Book

T. Akutsu,
Algorithms for Analysis, Inference, and Control of Boolean Networks,
World Scientific, 2018.
Journal Papers

T. Akutsu and A. A. Melkman,
On the size and width of the decoder of a Boolean threshold autoencoder
(Brief Paper),
IEEE Transactions on Neural Networks and Learning Systems, in press.

W. Someya, T. Akutsu, J. M. Schwartz, and J. C. Nacher,
Measuring criticality in control of complex biological networks,
NPJ Systems Biolohy and Applications, 10(1), 9 (16 pages), 2024.
 L. Mu, J. Song, T. Akutsu, and T. Mori,
DiCleave: a deep learning model for predicting human Dicer cleavage sites,
BMC Bioinformatics, 25(1), 13 (15 pages), 2024.

Y. Cui, Z. Wang, X. Wang, Y. Zhang, Y. Zhang, T. Pan, Z. Zhang, S. Li,
Y. Guo, T. Akutsu, and J. Song,
SMG: selfsupervised masked graph learning for cancer gene identification
(Problem Solving Protocol),
Briefings in Bioinformatics, 24(6), bbad406 (13 pages), 2023.

K. Shiota K and T. Akutsu,
Multishelled ECIF: improved extended connectivity interaction
features for accurate binding affinity prediction,
Bioinformatics Advances, 3(1), vbad155 (9 pages), 2023.

K. Matsuda, A. Shirakami, R. Nakajima, T. Akutsu, and M. Shimono,
Wholebrain evaluation of cortical microconnectomes,
eNeuro, 10(10), ENEURO.009423.2023 (17 pages), 2023.

Y. Cao, W. Pi, CY. Lin, U. Münzner, M. Ohtomo, and T. Akutsu,
Common attractors in multiple Boolean networks,
IEEE/ACM Transactions on Computational Biology and Bioinformatics,
20(5), 28622873, 2023.

F. Li, C. Wang, X. Guo, T. Akutsu, G. I. Webb, L. J. M. Coin, L. Kurgan, and
J. Song J,
ProsperousPlus: a onestop and comprehensive platform for accurate
proteasespecific substrate cleavage prediction and machinelearning
model construction (Problem Solving Protocol),
Briefings in Bioinformatics, 24(6), bbad372 (14 pages) , 2023.

K. Shiota, A. Suma, H. Ogawa, T. Yamaguchi, A. Iida, T. Hata, M. Matsushita, T. Akutsu, and M. Tateno,
AQDnet: Deep neural network for proteinligand docking simulation,
ACS Omega. 2023(8), 2392523935, 2023.

J. Xu, F. Li, C. Li, X. Guo, C. Landersdorfer, HH. Shen, A. Y. Peleg,
J. Li, S. Imoto, J. Yao, T. Akutsu, and J. Song,
iAMPCN: a deeplearning approach for identifying antimicrobial peptides
and their functional activities (Problem Solving Protocol).
Briefings in Bioinformatics, 24(4), bbad240 (20 pages), 2023.

X. Jia, P. Zhao, F. Li, Z. Qin, H. Ren, J. Li, C. Miao, Q. Zhao,
T. Akutsu, G. Dou, Z. Chen, and J. Song,
ResNetKhiib: a novel cell typespecific tool for predicting lysine
2hydroxyisobutylation sites via transfer learning
(Problem Solving Protocol),
Briefings in Bioinformatics, 24(2), bbad063 (13 pages), 2023.

T. Mori, T. Takase, KC. Lan, J. Yamane, C. Alev, A. Kimura, K. Osafune, J. K. Yamashita, T. Akutsu, H. Kitano, and W. Fujibuchi,
eSPRESSO: topological clustering of singlecell transcriptomics data to reveal informative genes for spatiotemporal architectures of cells,
BMC Bioinformatics, 24(1), 252 (27 pages), 2023.

T. Pan, C. Li, Y. Bi, Z. Wang, R. B. Gasser, A. N. Purcell, T. Akutsu,
G. I. Webb, S. Imoto, and J. Song,
PFresGO: an attention mechanismbased deeplearning approach for
protein annotation by integrating gene ontology interrelationships,
Bioinformatics, 39(3), btad094 (8 pages), 2023.

A. A. Melkman, S. Guo, WK. Ching, P. Liu, and T. Akutsu,
On the compressive power of Boolean threshold autoencoders,
IEEE Transactions on Neural Networks and Learning Systems,
34(2), 921931, 2023.

J. Chen, G. Han, A. Xu, T. Akutsu, and H. Cai,
Identifying miRNAgene common and specific regulatory modules
for cancer subtyping by a highorder graph matching model,
IEEE/ACM Transactions on Computational Biology and Bioinformatics,
20(1), 421431, 2023.

F. Zhang, J. Zhu, R. Chiewvanichakorn, A. Shurbevski, H. Nagamochi,
and T. Akutsu,
A new approach to the design of acyclic chemical compounds using skeleton
trees and integer linear programming,
Applied Intelligence, 52(15), 1705817072, 2022.
Preliminary version has appeared in AIE/IEA 2020.

C. Liu, J. Song, H. Ogata, and T. Akutsu.
MSNet4mC: learning effective multiscale representations for identifying
DNA N4methylcytosine sites,
Bioinformatics, 38(23), 51605167, 2022.

R. Li, JY. Lee, JM. Yang, and T. Akutsu,
Densest subgraphbased methods for proteinprotein interaction
hot spot prediction,
BMC Bioinformatics, 23(1), 451 (12 pages), 2022.

J. Zhu, N. A. Azam, F. Zhang, A. Shurbevski, K. Haraguchi, L. Zhao, H. Nagamochi, and T. Akutsu,
A novel method for inferring chemical compounds with prescribed topological
substructures based on integer programming,
IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press.
19(6), 32333245, 2022.

Z. Chen, X. Liu, P. Zhao, C. Li, Y. Wang, F. Li, T. Akutsu, C. Bain,
R. B. Gasser, J. Li, Z. Yang, X. Gao, L. Kurgan, and J. Song,
iFeatureOmega: an integrative platform for engineering, visualization
and analysis of features from molecular sequences,
structural and ligand data sets,
Nucleic Acids Research (Web Server Issue), 50(W1), 434447, 2022.

S. Iqbal, F. Ge, F. Li, T. Akutsu, Y. Zheng, R. B. Gasser, D. J. Yu, G. I. Webb, and J. Song,
PROST: AlphaFold2aware sequencebased predictor to estimate protein
stability changes upon missense mutations,
Journal Chemical Information and Modeling, 62(17), 42704282, 2022.

S. Guo, P. Liu, WK. Ching, and T. Akutsu,
On the distribution of successor states in Boolean threshold networks,
IEEE Transactions on Neural Networks and Learning Systems, 33(9), 41474159, 2022.

J. Zhu, N. A. Azam, K. Haraguchi, L. Zhao, H. Nagamochi, and T. Akutsu,
An inverse QSAR method based on linear regression and integer programming,
Frontiers in BioscienceLandmark, 77(6), 188 (14 pages), 2022.
Preliminary version has appeared in ICBBB 2022.

T. Mori and T. Akutsu,
Attractor detection and enumeration algorithms for Boolean networks (Mini Review),
Computational and Structural Biotechnology Journal, 20. 25122520, 2022.

M. Zhang, C. Jia, F. Li, C. Li, Y. Zhu, T. Akutsu, G. I. Webb, Q. Zou, L. J. M. Coin, and J. Song,
Critical assessment of computational tools for prokaryotic and eukaryotic promoter prediction (Review),
Briefings Bioinformatics, 23(2), bbab551 (25 pages), 2022.

G. V. Trinh, T. Akutsu, and K. Hiraishi,
An FVSbased approach to attractor detection in asynchronous random Boolean networks,
IEEE/ACM Transactions on Computational Biology and Bioinformatics,
19(2), 806818, 2022.

S. Kumano and T. Akutsu,
Comparison of the representational power of random forests, binary decision diagrams, and neural networks,
Neural Computation, 34(4), 10191044, 2022.

U. Münzner, T. Mori, M. Krantz, E. Klipp, and T. Akutsu,
Identification of periodic attractors in Boolean networks using a priori information,
PLoS Computational Biology, 18(1), e1009702 (27 pages), 2022.

F. Wang, YT. Chen, JM. Yang, and T. Akutsu,
A novel graph convolutional neural network for predicting interaction
sites on protein kinase inhibitors in phosphorylation,
Scientific Reports, 12(1), 229 (11 pages), 2022.

Y. Wang, F. Li, M. Bharathwaj, N. C. Rosas, A. Leier, T. Akutsu, G. I. Webb, T. T. MarquezLago, J. Li, T. Lithgow, and J. Song,
DeepBL: a deep learningbased approach for in silico discovery of betalactamases (Problem Solving Protocol),
Briefings in Bioinformatics, 22(4), bbaa301 (12 pages), 2021.

Y. Zhu, F. Li, D. Xiang, T. Akutsu, J. Song, and C. Jia,
Computational identification of eukaryotic promoters based on cascaded
deep capsule neural networks (Problem Solving Protocol),
Briefings in Bioinformatics, 22(4), bbaa299 (11pages), 2021.

H. Nagamochi, J. Zhu, N. A. Azam, K. Haraguchi, L. Zhao, and T. Akutsu,
Integer linear programmingbased methods for inverse QSAR (in Japanese),
Journal of Computer Chemistry, Japan, 20(3), 106111, 2021.

E. Yamaguchi, T. Akutsu, and J. C. Nacher,
Probabilistic critical controllability analysis of protein interaction networks
integrating normal brain ageing gene expression profiles,
International Journal of Molecular Sciences, 22(18), 9891, 2021.

N. Nakajima, T. Hayashi, K. Fujiki, K. Shirahige, T. Akiyama, T. Akutsu, and R. Nakato,
Codependency and mutual exclusivity for gene community detection from sparse singlecell transcriptome data,
Nucleic Acids Research, 49(18), e104 (13 pages), 2021.

S. Iqbal, F. Li, T. Akutsu, D. B. Ascher, G. I. Webb, and J. Song,
Assessing the performance of computational predictors for estimating
protein stability changes upon missense mutations (Review Article),
Briefings in Bioinformatics, 22(6), bbab184 (23 pages), 2021.

S. Mei, F. Li, D. Xiang, R. Ayala, P. Faridi, G. I. Webb, P. T. Illing, J. Rossjohn,
T. Akutsu, N. P. Croft, A. N. Purcell, and J. Song,
Anthem: a user customised tool for fast and accurate prediction of binding
between peptides and HLA class I molecules (Problem Solving Protocol),
Briefings in Bioinformatics, 22(5), bbaa415 (16 pages), 2021.

N. A. Azam, J. Zhu, Y. Sun, Y. Shi, A. Shurbevski, L. Zhao, H. Nagamochi, and T. Akutsu,
A novel method for inference of acyclic chemical compounds with bounded
branchheight based on artificial neural networks and integer programming,
Algorithms for Molecular Biology, 16(1), 18 (39 pages), 2021.

T. Akutsu, J. Jansson, R. Li, A. Takasu, and T. Tamura,
New and improved algorithms for unordered tree inclusion,
Theoretical Computer Science, 883, 8398, 2021.
Preliminary version has appeared in ISAAC 2018.

R. Xie, J. Li, J. Wang, W. Dai, A. Leier, T. T. MarquezLago, T. Akutsu, T. Lithgow, J. Song, and Y. Zhang,
DeepVF: a deep learningbased hybrid framework for identifying virulence factors using the stacking strategy (Problem Solving Protocol),
Briefings in Bioinformatics, 22(3), bbaa125 (15 pages), 2021.

X. Cheng, WK. Ching, S. Guo, and T. Akutsu,
Discrimination of attractors with noisy nodes in Boolean networks
(Technical Communique),
Automatica, 130, 109630, 2021.

Z. Chen, P. Zhao, C. Li, F. Li, D. Xiang, Y. Z. Chen, T. Akutsu, R. J. Daly RJ,
G. I. Webb, Q. Zhao, L. Kurgan, and J. Song,
iLearnPlus: a comprehensive and automated machinelearning platform
for nucleic acid and protein sequence analysis, prediction and visualization,
Nucleic Acids Research, 49(10), e60, 2021.

T. Shinzawa, T. Akutsu, and J. C. Nacher,
Uncovering and classifying the role of driven nodes in control of complex networks,
Scientific Reports, 11(1), 9627, 2021.

M. Kajiwara, R. Nomura, F. Goetze, M. Kawabata, Y. Isomura, T. Akutsu, and M. Shimono,
Inhibitory neurons exhibit high controlling ability in the cortical microconnectome,
PLoS Computational Biology, 17(4), e1008846, 2021.

R. Li, CY. Lin, WF. Guo, and T. Akutsu,
Weighted minimum feedback vertex sets and implementation
in human cancer genes detection,
BMC Bioinformatics, 22(1), 143, 2021.

Y. Shi, J. Zhu, N. A. Azam, K. Haraguchi, L. Zhao, H. Nagamochi, and T. Akutsu,
An inverse QSAR method based on a twolayered model and integer programming,
International Journal of Molecular Sciences, 22, 2847, 2021.

P. Liu, J. Song, CY. Lin, and T. Akutsu,
ReCGBM: a gradient boostingbased method for predicting human Dicer cleavage sites,
BMC Bioinformatics, 22(1), 63, 2021.
 F. Wang, T. Akutsu, and T. Mori,
Comparison of pseudoknotted RNA secondary structures by topological centroid
identification and tree edit distance,
Journal of Computational Biology, 27(9), 14431451, 2020.
 Z. Chen, P. Zhao, F. Li, Y. Wang, A. I. Smith, G. I. Webb, T. Akutsu, A. Baggag, H. Bensmail, and J. Song,
Comprehensive review and assessment of computational methods for predicting RNA posttranscriptional modification sites from RNA sequences (Review Article),
Briefings in Bioinformatics, 21(5), 16761696, 2020.
 F. Li, A. Leier, Q. Liu, Y. Wang, D. Xiang, T. Akutsu, G. I. Webb, A. I. Smith, T. MarquezLago, J. Li, and J. Song,
Procleave: predicting proteasespecific substrate cleavage sites by combining sequence and structural information,
Genomics, Proteomics & Bioinformatics, 18(1), 5264, 2020.

WF, Guo, SW. Zhang, T. Zeng, T. Akutsu, and L. Chen,
Network control principles for identifying personalized driver genes in cancer (Review Article),
Briefings in Bioinformatics, 21(5), 16411662, 2020.

S. Mei, F. Li, A. Leier, T. T. MarquezLago, K. Giam, N. P. Croft, T. Akutsu,
A. I. Smith, J. Li, J. Rossjohn, A. W. Purcell, and J. Song,
A comprehensive review and performance evaluation of bioinformatic
tools for HLA class I peptide binding prediction (Review Article),
Briefings in Bioinformatics, 21(4), 11191135, 2020.

Z. Chen, P. Zhao, F. Li, T. T. MarquezLago, A. Leier, J. Revote, Y. Zhu, D. R. Powell, T. Akutsu, G. I. Webb, K. C. Chou, A. T. Smith, R. J. Daly, J. Li,
and J. Song,
iLearn: an integrated platform and metalearner for feature engineering, machinelearning analysis and modeling of DNA, RNA and protein sequence data
(Problem Solving Protocol),
Briefings in Bioinformatics, 21(3), 10471057, 2020.

J. Zhu, C. Wang, A. Shurbevski, H. Nagamochi, and T. Akutsu,
A novel method for inference of chemical compounds of cycle index two
with desired properties based on artificial neural networks and integer
programming,
Algorithms, 13, 124 (30 pages), 2020.

P. Liu, A. A. Melkman, and T. Akutsu,
Extracting Boolean and probabilistic rules from trained neural networks,
Neural Networks, 126, 300311, 2020.

T. Akutsu, A. A. Melkman, and T. Tamura,
Improved hardness of maximum common subgraph problems on labeled
graphs of bounded treewidth and bounded degree,
International Journal of Foundations of Computer Science,
31(2), 253273, 2020.

F. Li, J. Chen, A. Leier, T. MarquezLago, Q. Liu, Y. Wang, J. Revote, A. I. Smith, T. Akutsu, G. I. Webb, L. Kurgan, and J. Song,
DeepCleave: a deep learning predictor for caspase and matrix metalloprotease
substrates and cleavage sites,
Bioinformatics, 36(4), 10571065, 2020.

S. Nakashima, J. C. Nacher, J. Song, and T. Akutsu,
An overview of bioinformatics methods for analyzing autism spectrum disorders (Review Article),
Current Pharmaceutical Design, 25(43), 45524559, 2020.

Y. Zhang, S. Yu, R. Xie, J. Li, A. Leier, T. T. MarquezLago, T. Akutsu, A. I. Smith, Z. Ge, J. Wang, T. Lithgow, and J. Song,
PeNGaRoo, a combined gradient boosting and ensemble learning framework
for predicting nonclassical secreted proteins,
Bioinformatics. 36(3), 704712, 2020.

J. Zeng, H. Cai, H. Peng, H. Wang, Y. Zhang, and T. Akutsu,
Causalcall: nanopore basecalling using a temporal convolutional network,
Frontiers in Genetics, 10, 1332 (11 pages), 2020.

Y. Zhang, R. Xie, J. Wang, A. Leier, T. T. MarquezLago, T. Akutsu, G. I. Webb, K. C. Chou, and J. Song,
Computational analysis and prediction of lysine malonylation sites
by exploiting informative features in an integrative machinelearning framework (Opinion Article),
Briefings in Bioinformatics, 20(6), 21852199, 2019.

Z. Chen, X. Liu, F. Li, C. Li, T. MarquezLago, A. Leier, T. Akutsu, G. I. Webb, D. Xu, A. I. Smith, L. Li, K. C. Chou, and J. Song,
Largescale comparative assessment of computational predictors for lysine posttranslational modification sites (Review Article),
Briefings in Bioinformatics, 20(6), 22672290, 2019.

F. Li, Y, Wang, C. Li, T. T. MarquezLago, A. Leier, N. D. Rawlings, G. Haffari, J. Revote, T. Akutsu, K. C. Chou, A. W. Purcell, R. N. Pike, G. I. Webb,
A. Ian Smith, T. Lithgow, R. J. Daly, J. C. Whisstock, and J. Song,
Twenty years of bioinformatics research for proteasespecific substrate
and cleavage site prediction: a comprehensive revisit and benchmarking
of existing methods (Review Article),
Briefings in Bioinformatics, 20(6), 21502166, 2019.

Y. Bao, S. Marini, T. Tamura, M. Kamada, S. Maegawa, H. Hosokawa, J. Song, and T. Akutsu,
Toward more accurate prediction of caspase cleavage sites: a comprehensive review of current methods, tools and features (Review Article),
Briefings in Bioinformatics, 20(5), 16691684, 2019.
 S. ItamiMatsumoto, M. Hayakawa, S. UchidaKobayashi, M. Enomoto, A. Tamori, K. Mizuno, H. Toyoda, T. Tamura, T. Akutsu, T. Ochiya, N. Kawada, and Y. Murakami,
Circulating exosomal miRNA profiles predict the occurrence and recurrence of hepatocellular carcinoma in patients with directacting antiviralinduced sustained viral response,
Biomedicines. 7(4), 87, 2019.

H. Koyano, M. Hayashida, and T. Akutsu,
Optimal string clustering based on a Laplacelike mixture and EM algorithm on a set of strings,
Journal of Computer and System Sciences,
106 94128, 2019.

T. Akutsu and A. A. Melkman,
Identification of the structure of a probabilistic Boolean network from samples including frequencies of outcomes,
IEEE Transactions on Neural Networks and Learning Systems,
30(8), 23832396, 2019.

CY. Lin, P. Ruan, R. Li, JM. Yang, S. See, J. Song, and T. Akutsu,
Deep learning with evolutionary and genomic profiles for identifying cancer subtypes,
Journal of Bioinformatics and Computational Biology, 17(3)
(Special Section on CBIM2018), 1940005 (15 pages), 2019.

T. Matsubara, T. Ochiai, M. Hayashida, T. Akutsu, and J. C. Nacher,
Convolutional neural network approach to lung cancer classification
integrating protein interaction network and gene expression profiles,
Journal of Bioinformatics and Computational Biology, 17(3)
(Special Section on CBIM2018), 1940007 (11 pages), 2019.

J. Wang, B. Yang, Y. An, T. MarquezLago, A. Leier, J. Wilksch, Q. Hong,
Y. Zhang, M. Hayashida, T. Akutsu, G. I. Webb, R, A. Strugnell, J. Song,
and T. Lithgow,
Systematic analysis and prediction of type IV secreted effector proteins
by machine learning approaches,
Briefings in Bioinformatics, 20(3), 931951, 2019.

JM. Schwartz, H. Otokuni, T. Akutsu, and J. C. Nacher,
Probabilistic controllability approach to metabolic
fluxes in normal and cancer tissues,
Nature Communications, 10, 2725 (9 pages), 2019.

J. Wang, J. Li, B. Yang, R. Xie, T. T. MarquezLago, A. Leier, M. Hayashida, T. Akutsu, Y. Zhang, K. C. Chou, J. Selkrig, T. Zhou, J. Song, and T. Lithgow,
Bastion3: a twolayer ensemble predictor of type III secreted effectors,
Bioinformatics, 35, 20172028, 2019.

J. Song, Y. Wang, F. Li, T. Akutsu, N. D. Rawlings, G. I. Webb, and K. C. Chou,
iProtSub: a comprehensive package for accurately mapping and predicting
proteasespecific substrates and cleavage sites (Review Article),
Briefings in Bioinformatics, 20, 638658, 2019.

S. Marini, F. Vitali, S. Rampazzi, A. Demartini, and T. Akutsu,
Protease target prediction via matrix factorization,
Bioinformatics, 35(6), 923929, 2019.

V, Ravindran, J. C. Nacher, T. Akutsu, M. Ishitsuka,
A. Osadcenco, V. Sunitha, G. Bagler, JM. Schwartz, and
D. L. Robertson,
Network controllability analysis of intracellular signalling reveals
viruses are actively controlling molecular systems,
Scientific Reports, 9, 2066, 2019.

Y. Nishiyama, A. Shurbevski, H. Nagamochi, and T. Akutsu,
Resource cut, a new bounding procedure to algorithms for enumerating
treelike chemical graphs,
IEEE/ACM Transactions on Computational Biology and Bioinformatics,
16(1), 7790, 2019.

J. C. Nacher, M. Ishitsuka, S. Miyazaki, and T. Akutsu,
Finding and analysing the minimum set of driver nodes required to control multilayer networks,
Scientific Reports, 9(1), 576 (12 pages), 2019.

W. Hou, P. Ruan, WK. Ching, and T. Akutsu,
On the number of driver nodes for controlling a Boolean network when the targets are restricted to attractors,
Journal of Theoretical Biology, 463, 111, 2019.

F. Li, C. Li, T. T. MarquezLago, A. Leier, T. Akutsu, A. W. Purcell,
A. I. Smith, T. Lithgow, R. Daly, J. Song, and K. C. Chou,
Quokka: a comprehensive tool for rapid and accurate prediction of
kinase familyspecific phosphorylation sites in the human proteome,
Bioinformatics, 4, 42234231, 2018.

T, Tamura, W. Lu, J. Song, and T. Akutsu,
Computing minimum reaction modifications in a Boolean metabolic network,
IEEE/ACM Transactions on Computational Biology and Bioinformatics,
15(2) (Special Section for GIW/InCoB 2015),
18531862, 2018.

Y. Bao, M. Hayashida, P. Liu, M. Ishitsuka, J. C. Nacher, and T. Akutsu,
Analysis of critical and redundant vertices in controlling directed complex
networks using feedback vertex sets,
Journal of Computational Biology, 25, 10711090, 2018.

J. Wang, B. Yang, A. Leier, T. T. MarquezLago, M. Hayashida, A. Rocker,
Z. Yanju, T. Akutsu, K. C. Chou, R. A. Strugnell, J. Song, and T. Lithgow,
Bastion6: a bioinformatics approach for accurate prediction of type
VI secreted effectors,
Bioinformatics, 34(15), 25462555, 2018.

T. Mori, H. Ngouv, M. Hayashida, T. Akutsu, and J. C. Nacher,
ncRNAdisease association prediction based on sequence information
and tripartite network,
BMC Systems Biology 12, Suppl 1 (Supplement for APBC 2018),
37 (11 pages), 2018.

N. Nakajima, M. Hayashida, J. Jansson, O. Maruyama, and T. Akutsu,
Determining the minimum number of proteinprotein interactions
required to support known protein complexes,
PLoS One, 13(4), e0195545 (17 pages), 2018.

J. Li, H. Nagamochi, and T. Akutsu,
Enumerating substituted benzene isomers of treelike chemical graphs,
IEEE/ACM Transactions on Computational Biology and Bioinformatics,
15(2), 633646, 2018.

A. A. Melkman, X. Cheng, WK. Ching, and T. Akutsu,
Identifying a probabilistic Boolean threshold network from samples,
IEEE Transactions on Neural Networks and Learning Systems,
29(4), 869881, 2018.

P. Ruan, M. Hayashida, T. Akutsu, and JP. Vert,
Improving prediction of heterodimeric protein complexes using
combination with pairwise kernel,
BMC Bioinformatics, 19, Suppl 1 (Supplement for GIW 2017),
7384, 2018.

J. Song, F. Li, A. Leier, T. T. MarquezLago. T. Akutsu, G. Haffari, KC. Chou, G. I. Webb, and R. N. Pike,
PROSPERous: highthroughput prediction of substrate cleavage sites
for 90 proteases with improved accuracy (Applications Note),
Bioinformatics, 34(4), 684687, 2018.

L. Liu, T. Mori, Y. Zhao, M. Hayashida, and T. Akutsu,
Euler stringbased compression of treestructured data and
its application to analysis of RNAs,
Current Bioinformatics, 13(1), 2533, 2018.

J. Song, F. Li, K. Takemoto, G. HaHaffari, T. Akutsu, KC. Chou, and G. I. Webb.
PREvaIL, an integrative approach for inferring catalytic residues using
sequence, structural, and network features in a machinelearning framework.
Journal of Theoretical Biology, 443, 125137, 2018.

M. Ishitsuka, T. Akutsu and J. C. Nacher,
Critical controllability analysis of directed biological networks
using efficient graph reduction,
Scientific Reports, 7, 14361 (10 pages), 2017.

J. Song, H. Wang, J. Wang, A, Leier, T. MarquezLago, B. Yang,
Z. Zhang, T. Akutsu, G. I. Webb and R. J. Daly,
PhosphoPredict: A bioinformatics tool for prediction of human kinasespecific
phosphorylation substrates and sites by integrating heterogeneous feature
selection,
Scientific Reports, 7, 6862 (19 pages), 2017.

F. Li, J. Song, C. Li, T. Akutsu and Y. Zhang,
PAnDE: Averaged ndependence estimators for positive unlabeled learning,
ICIC Express Letters, Part B: Applications, 8, 12871297, 2017.

X. Cheng, T. Tamura, WK. Ching and T. Akutsu.
Discrimination of singleton and periodic attractors in Boolean networks,
Automatica, 84, 205213, 2017.

T. Akutsu, J. Jansson, A. Takasu and T. Tamura,
On the parameterized complexity of associative and commutative unification,
Theoretical Computer Science, 660, 5774, 2017.
Preliminary version has appeared in IPEC 2014.

Y. An, J. Wang, J. Song, C. Li, J. Revote, T. Naderer, M. Hayashida, T. Akutsu, Y. Zhang, G. I. Webb and T. Lithgow,
SecretEPDB: a comprehensive webbased resource for secreted effector proteins of the bacterial types III, IV and VI secretion systems,
Scientific Reports, 7, 41031 (10 pages), 2017.

Y. Kato, T. Mori, K. Sato, S. Maegawa, H. Hosokawa and T. Akutsu,
An accessibilityincorporated method for accurate prediction of
RNARNA interactions from sequence data,
Bioinformatics, 33, 202209, 2017.

X. Cheng, T. Mori, Y. Qiu, WK. Ching and T. Akutsu,
Exact identification of the structure of a probabilistic Boolean network from samples,
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 13, 11071116, 2016.

Y. Bao, M. Hayashida and T. Akutsu,
LBSizeCleav: improved support vector machine (SVM)based prediction of
Dicer cleavage sites using loop/bulge length,
BMC Bioinformatics, 17, 487 (11 pages), 2016.

W. Hou, T. Tamura, WK. Ching and T. Akutsu,
Finding and analyzing the minimum set of driver nodes in control of
Boolean networks,
Advances in Complex Systems, 19, 1650006 (32 pages), 2016.

J. Jindalertudomdee, M. Hayashida and T. Akutsu,
Enumeration method for structural isomers containing
userdefined structures based on breadthfirst search approach,
Journal of Computational Biology, 23, 625640, 2016.

K. Takemoto and T. Akutsu,
Analysis of the effect of degree correlation on the size of minimum
dominating sets in complex networks,
PLoS ONE, 11(6), e0157868 (11 pages), 2016.

M. Hayashida and T. Akutsu,
Complex networkbased approaches to biomarker discovery (Review Paper),
Biomarkers in Medicine, 10(6), 621632, 2016.

J. C. Nacher and T. Akutsu,
Minimum dominating setbased methods for analyzing biological networks (Invited Review Paper),
Methods, 102, 5763, 2016.

M. Ishitsuka, T. Akutsu and J. C. Nacher,
Critical controllability in proteomewide protein interaction network
integrating transcriptome,
Scientific Reports, 6, 23541 (13 pages), 2016.

H. Koyano, M. Hayashida and T. Akutsu,
Maximum margin classifier working in a set of strings,
Proceedings of the Royal Society A, 472, 20150551 (17 pages), 2016.

C. Li, C. C. H. Chang, B. T. Porebski, M. Hayashida, T. Akutsu, J. Song and A. M. Buckle,
Critical evaluation of in silico methods for prediction of coiledcoil domains in proteins (Review Paper),
Briefings in Bioinformatics, 17. 270282, 2016.

J. Jindalertudomdee, M. Hayashida, Y. Zhao and T. Akutsu,
Enumeration method for treelike chemical compounds
with benzene rings and naphthalene rings by breadthfirst search order,
BMC Bioinformatics, 17, 113 (16 pages), 2016.

T. Hasegawa, A. Niida, T. Mori, T. Shimamura, R. Yamaguchi,
S. Miyano, T. Akutsu and S. Imoto,
A likelihoodfree filtering method via approximate Bayesian computation
in evaluating biological simulation models,
Computational Statistics and Data Analysis, 94, 6374, 2016.

H. Kagami, T. Akutsu, S. Maegawa, H. Hosokawa and J. C. Nacher,
Determining associations between human diseases and noncoding RNAs with
critical roles in network control,
Scientific Reports, 5, 14577 (11 pages), 2015.

X. Cong and T. Akutsu,
Matrix Network: a new data structure for efficient enumeration of microstates
of a genetic regulatory network,
Journal of Information Processing, 23, 804813, 2015.

T. Mori, A. Takasu, J. Jansson, J. Hwang, T. Tamura and T. Akutsu,
Similar subtree search using extended tree inclusion,
IEEE Transactions on Knowledge and Data Engineering, 27, 33603373, 2015.

T. Mori, M. Floettmann, M. Krantz, T. Akutsu and E. Klipp,
Stochastic simulation of Boolean rxncon models:
towards quantitative analysis of large signaling networks,
BMC Systems Biology, 9, 45 (9 pages), 2015.

T. Akutsu, T. Tamura, A. A. Melkman and A. Takasu,
On the complexity of finding a largest common subtree of bounded degree,
Theoretical Computer Science, 590. 216, 2015.
Preliminary version has appeared in FCT 2013.

T. Tamura, W. Lu and T. Akutsu,
Computational methods for modification of metabolic networks (Invited MiniReview Paper),
Computational and Structural Biotechnology Journal, 13. 376381, 2015.

M. Hayashida, J. Jindalertudomdee, Y. Zhao and T. Akutsu,
Parallelization of enumerating treelike chemical compounds by breadthfirst search order,
BMC Medical Genomics, 8, Suppl 2 (Suppl for TBC/ISB 2014), S15 (7 pages), 2015.

Y. Zhao, M. Hayashida, Y. Cao, J. Hwang and T. Akutsu,
Grammarbased compression approach to extraction of common rules
among multiple trees of glycans and RNAs,
BMC Bioinformatics, 16, 128 (13 pages), 2015.

T. Hasegawa, T. Mori, R. Yamaguchi, T. Shimamura, S. Miyano, S. Imoto and T. Akutsu,
Genomic data assimilation using a higher moment filtering technique for
restoration of gene regulatory networks,
BMC Systems Biology, 9, 14 (13 pages), 2015.

W. Lu, T. Tamura, J. Song and T. Akutsu,
Computing smallest intervention strategies for multiple metabolic
networks in a Boolean model,
Journal of Computational Biology, 22, 85110, 2015.

L. Uechi, T. Akutsu, H. E. Stanley, A. J. Marcus and D. Y. Kenett,
Sector dominance ratio analysis of financial markets,
Physica A, 421, 488509, 2015.

J. C. Nacher and T. Akutsu,
Structurally robust control of complex networks,
Physical Review E, 91, 012826, 2015.

CJ. Chang, T. Tamura, KM. Chao and T. Akutsu,
A fixedparameter algorithm for detecting a singleton attractor in an
AND/OR Boolean network with bounded treewidth,
IEICE Transactions on Fundamentals of Electronics,
Communications and Computer Sciences, E98A, 384390, 2015.

J. C. Nacher and T. Akutsu,
Analysis of critical and redundant nodes in controlling
directed and undirected complex networks using dominating sets,
Journal of Complex Networks, 2, 394412, 2014.
Preliminary version has appeared in SITIS 2013.

T. Hasegawa, T. Mori, R. Yamaguchi, S. Imoto, S. Miyano and T. Akutsu,
An efficient data assimilation schema for restoration and extension of gene
regulatory networks using timecourse observation data,
Journal of Computational Biology, 21, 785798, 2014.

H. Koyano, T. Tsubouchi, H. Kishino and T. Akutsu,
Archaeal beta diversity patterns under the seafloor along geochemical gradients,
Journal of Geophysical Research  Biogeosciences, 119, 17701788, 2014.

M. Kamada, Y. Sakuma, M. Hayashida and T. Akutsu,
Prediction of proteinprotein interaction strength using domain
features with supervised regression,
The Scientific World Journal, 2014, 240673 (7 pages), 2014.
Preliminary version has appeared in PDPTA 2013.

M. Hayashida, P. Ruan and T. Akutsu,
Proteome compression via protein domain compositions,
Methods, 67, 380385, 2014.

M. Suzuki, H. Nagamochi and T. Akutsu,
Efficient enumeration of monocyclic chemical graphs with
given path frequencies,
Journal of Cheminformatics, 6, 31 (18 pages), 2014.

M. Hayashida and T. Akutsu,
Domainbased approaches to prediction and analysis of proteinprotein
interactions (Invited Review Paper),
International Journal of Knowledge Discovery in Bioinformatics,
4, 2441, 2014.

T. Akutsu, T. Tamura, D. Fukagawa and A. Takasu,
Efficient exponentialtime algorithms for edit distance between
unordered trees,
Journal of Discrete Algorithms, 25, 7993, 2014.
Preliminary version has appeared in CPM 2012.

N. Nakajima and T. Akutsu,
Network completion for static gene expression data,
Advances in Bioinformatics, 2014, 382452 (9 pages), 2014.

H. Cai, P. Ruan, M. Ng and T. Akutsu,
Feature weight estimation for gene selection:
a local hyperlinear learning approach,
BMC Bioinformatics, 15, 70 (13 pages), 2014.

W. Lu, T. Tamura, J. Song and T. Akutsu,
Integer programmingbased method for designing synthetic metabolic
networks by minimum reaction insertion in a Boolean model,
PLoS ONE, 9, e92637 (14 pages), 2014.

N. Nakajima and T. Akutsu,
Exact and heuristic methods for network completion for time varying
genetic networks,
BioMed Research International, 2014, 684014 (13 pages), 2014.
Preliminary version has appeared in IIBM 2013.

P. Ruan, M. Hayashida, O. Maruyama and T. Akutsu,
Prediction of heterotrimeric protein complexes by twophase learning
using neighboring kernels,
BMC Bioinformatics, 15, Suppl 2 (Suppl. for APBC 2014),
S6 (6 pages), 2014.

Y. Qiu, T. Tamura, WK. Ching and T. Akutsu,
On control of singleton attractors in multiple Boolean networks:
integer programmingbased method,
BMC Systems Biology, 8, Suppl 1 (Suppl. for APBC 2014), S7 (10 pages),
2014.

M. Wang, XM. Zhao, H. Tan, T. Akutsu, J. C. Whisstock and J. Song,
Cascleave 2.0,
a new approach for predicting caspase and granzyme cleavage targets,
Bioinformatics, 30, 7180, 2014.

Y. Zhao, M. Hayashida, J. Jindalertudomdee, H. Nagamochi and T. Akutsu,
Breadth first search approach to enumeration of treelike chemical
compounds,
Journal of Bioinformatics and Computational Biology,
11 (Special Issue for GIW 2013), 1343007 (19 pages), 2013.

M. Hayashida, M. Kamada, J. Song and T. Akutsu,
Prediction of proteinRNA residuebase contacts using twodimensional
conditional random field with the lasso,
BMC Systems Biology, 7, Suppl 2 (Suppl. for ISB 2012),
S15 (11 pages), 2013.
Preliminary version has appeared in ISB 2012.

A. A. Melkman and T. Akutsu,
An improved satisfiability algorithm for nested canalyzing functions and
its application to determining a singleton attractor of a Boolean network,
Journal of Computational Biology, 20, 958969, 2013.

H. Jiang, T. Tamura, WK. Ching and T. Akutsu,
On the complexity of inference and completion of Boolean networks
from given singleton attractors,
IEICE Transactions on Fundamentals of Electronics,
Communications and Computer Sciences, E96A,
22652274, 2013.

L. Uechi and T. Akutsu,
Stability and restoration phenomena in competitive systems,
Progress of Theoretical and Experimental Physics, 2013,
103J01 (18 pages), 2013.

K. Takemoto, T. Tamura and T. Akutsu,
Theoretical estimation of metabolic network robustness against
multiple reaction knockouts using branching process approximation,
Physica A, 392, 55255535, 2013.

Y. Zhao, T. Tamura, T. Akutsu and JP. Vert,
Flux balance impact degree: A new definition of impact
degree to properly treat reversible reactions in metabolic networks,
Bioinformatics, 29, 21782185, 2013.

M. Wang, Z. Sun, T. Akutsu and J. Song,
Recent advances in predicting functional impact of single amino acid
polymorphisms: a review of useful features, computational methods
and available tools (Review Paper),
Current Bioinformatics, 8, 161176, 2013.

P. Ruan, M. Hayashida, O. Maruyama and T. Akutsu,
Prediction of heterodimeric protein complexes from weighted proteinprotein
interaction networks using novel features and kernel functions,
PLoS ONE, 8, e65265 (7 pages), 2013.

Y. Lai, M. Hayashida and T. Akutsu,
Survival analysis by penalized regression and matrix factorization,
The Scientific World Journal, 2013, 632030 (11 pages), 2013.

J. C. Nacher and T. Akutsu,
Structural controllability of unidirectional bipartite networks,
Scientific Reports, 3, 1647 (8 pages), 2013.

X. Chen, T. Akutsu, T. Tamura and WK. Ching,
Finding optimal control policy in probabilistic Boolean networks
with hard constraints by using integer programming and dynamic programming,
International Journal of Data Mining and Bioinformatics, 7, 322343, 2013.
Preliminary version has appeared in BIBM 2010.

T. Akutsu and H. Nagamochi,
Comparison and enumeration of chemical graphs (Invited Review Paper),
Computational and Structural Biotechnology Journal,
5, e201302004 (9 pages), 2013.

T. Akutsu and T. Tamura,
A polynomialtime algorithm for computing the maximum common
connected edge subgraph of outerplanar graphs of bounded degree,
Algorithms, 6, 119135, 2013.
Preliminary version has appeared in MFCS 2012.

T. Akutsu, D. Fukagawa, M. M. Halldorsson, A. Takasu and K. Tanaka,
Approximation and parameterized algorithms for common subtrees and
edit distance between unordered trees,
Theoretical Computer Science, 470, 1022, 2013.
Preliminary results appeared in SPIRE 2009 (by DF, TA, AT) and
ISAAC 1996 (by MMH, KT).

J. Song, H. Tan, A. J. Perry, T. Akutsu, G. I. Webb, J. C. Whisstock
and R. N. Pike,
PROSPER: an integrated featurebased tool for predicting protease
substrate cleavage sites,
PLoS ONE, 7, e50300 (23 pages), 2012.

K. Sato, Y. Kato, T. Akutsu, K. Asai and Y. Sakakibara,
DAFS: simultaneous aligning and folding of RNA sequences via dual decomposition,
Bioinformatics, 28, 32183224, 2012.

T. Akutsu, Y. Zhao, M. Hayashida and T. Tamura,
Integer programmingbased approach to attractor detection and
control of Boolean networks,
IEICE Transactions on Information and Systems, E95D, 29602970, 2012.
Preliminary version has appeared in CDC/CCC 2009.

C. Zheng, M. Wang, K. Takemoto, T. Akutsu, Z. Zhang and J. Song,
An integrative computational framework based on a twostep random
forest algorithm improves prediction of zincbinding sites in proteins,
PLoS ONE, 7, e49716 (15 pages), 2012.

N. Nakajima, T. Tamura, Y. Yamanishi, K. Horimoto and T. Akutsu,
Network completion using dynamic programming and leastsquares fitting,
The Scientific World Journal, 2012, 957620 (8 pages), 2012.

T. Mori, T. Tamura, D. Fukagawa, A. Takasu, E. Tomita and T. Akutsu,
A cliquebased method using dynamic programming for computing edit
distance between unordered trees,
Journal of Computational Biology, 19, 10891104, 2012.

Y. Zhao, M. Hayashida, J. C. Nacher, H. Nagamochi and T. Akutsu,
Protein complex prediction via improved verification methods
using constrained domaindomain matching,
International Journal of Bioinformatics Research and Applications,
8, 210227, 2012.

T. Akutsu, S. Kosub, A. A. Melkman and T. Tamura,
Finding a periodic attractor of a Boolean network,
IEEE/ACM Transactions on Computational Biology and Bioinformatics,
9, 14101421, 2012.

M. Wang, XM. Zhao, K. Takemoto, H. Xu, Y. Li, T. Akutsu and J. Song,
FunSAV: predicting the functional effect of single amino acid variants
using a twostage random forest model,
PLoS ONE, 7, e43847 (14 pages), 2012.

J. C. Nacher and T. Akutsu,
Dominating scalefree networks with variable scaling exponent:
Heterogeneous networks are not difficult to control,
New Journal of Physics, 14, 073005, 2012.

Y. Kato, K. Sato, K. Asai and T. Akutsu,
Rtips: fast and accurate tools for RNA 2D structure prediction using
integer programming,
Nucleic Acids Research, 40, Web Server Issue, W29W34, 2012.

L. Uechi and T. Akutsu,
Conservation laws and symmetries in competitive systems,
Progress of Theoretical Physics Supplement, No. 194, 210222, 2012.
(Proc. the YITP Workshop on Econophysics)

T. Akutsu, D. Fukagawa, J. Jansson and K. Sadakane,
Inferring a graph from path frequency,
Discrete Applied Mathematics, 160, 14161428, 2012.
Preliminary version has appeared in CPM 2005.

M. Hayashida, P. Ruan and T. Akutsu,
A quadsection algorithm for grammarbased image compression,
Integrated ComputerAided Engineering, 19, 2338, 2012.
Preliminary version has appeared in Proc. FGIT 2010.

J. Song, H. Tan, M. Wang, G. I. Webb and T. Akutsu,
Twolevel support vector regression approach for protein backbone
torsion angle prediction from primary sequences,
PLoS ONE, 7, e30361 (16 pages), 2012.

T. Akutsu, A. A. Melkman and T. Tamura,
Singleton and 2periodic attractors of signdefinite Boolean networks,
Information Processing Letters, 112, 3538, 2012.

K. Takemoto, T. Tamura, Y. Cong, WK. Ching, JP. Vert and T. Akutsu,
Analysis of the impact degree distribution in metabolic
networks using branching process approximation,
Physica A, 391, 379397, 2012.

M. Shimizu, H. Nagamochi and T. Akutsu,
Enumerating treelike chemical graphs with given upper and
lower bounds on path frequencies,
BMC Bioinformatics, 12, Suppl 14 (Suppl. for GIW 2011), S3 (9 pages), 2011.

T. Tamura, Y. Cong, T. Akutsu and WK. Ching,
An efficient method of computing impact degrees for multiple
reactions in metabolic networks with cycles,
IEICE Transactions on Information and Systems, E94D, 23932399, 2011.
Preliminary version has appeared in DTMBIO 2009.

M. Hayashida and T. Akutsu,
Measuring the similarity of protein structures using image compression algorithms,
IEICE Transactions on Information and Systems, E94D, 24682478, 2011.
Preliminary version has appeared in APBC 2008.

U. Poolsap, Y. Kato, K. Sato and T. Akutsu,
Using binding profiles to predict RNA binding sites of target RNAs,
Journal of Bioinformatics and Computational Biology, 9, 697713, 2011.
Preliminary version has appeared in PSB 2010.

T. Imada, S. Ota, H. Nagamochi and T. Akutsu,
Efficient enumeration of stereoisomers of outerplanar chemical graphs
using dynamic programming,
Journal of Chemical Information and Modeling, 51, 27882807, 2011.

O. DemirKavuk, M. Kamada, T. Akutsu and EW. Knapp,
Prediction using stepwise L1, L2 regularization and
feature selection for small data sets with large number of features,
BMC Bioinformatics, 12, 412 (10 pages), 2011.

T. Akutsu and H. Nagamochi,
Kernel methods for chemical compounds: From classification to design (Invited Survey Paper),
IEICE Transactions on Information and Systems, E94D, 18461853, 2011.

T. Akutsu, A. A. Melkman, T. Tamura and M. Yamamoto,
Determining a singleton attractor of a Boolean network with nested canalyzing functions,
Journal of Computational Biology, 18, 12751290, 2011.

J. C. Nacher and T. Akutsu,
On the degree distribution of projected networks mapped from
bipartite networks,
Physica A, 390, 46364651, 2011.

M. Hayashida, M. Kamada, J. Song and T. Akutsu,
Conditional random field approach to prediction of
proteinprotein interactions using domain information,
BMC Systems Biology, 5, Suppl. 1, S8 (9 pages), 2011.
Preliminary version has appeared in ISB 2010.

K. Sato, Y. Kato, M. Hamada, T. Akutsu and K. Asai,
IPknot: fast and accurate prediction of RNA secondary structures with
pseudoknots using integer programming,
Bioinformatics (Suppl. for ISMB/ECCB 2011), 27, i85i93, 2011.

T. Imada, S. Ota, H. Nagamochi and T. Akutsu,
Efficient enumeration of stereoisomers of tree structured molecules using dynamic programming,
Journal of Mathematical Chemistry, 49, 910970, 2011.

D. Fukagawa, T. Tamura, A. Takasu, E. Tomita and T. Akutsu,
A cliquebased method for the edit distance between unordered trees and its application
to analysis of glycan structures,
BMC Bioinformatics,
12, Suppl 1 (Suppl. for APBC 2011), S14 (9 pages), 2011.

J. Song, H. Tan, S. E. Boyd, H. Shen, K. Mahmood, G. I. Webb, T. Akutsu, J. C. Whisstock and R. N. Pike,
Bioinformatic approaches for predicting substrates of proteases (Invited Review Paper),
Journal of Bioinformatics and Computational Biology, 9, 149178, 2011.

T. Akutsu, D. Fukagawa, A. Takasu and T. Tamura,
Exact algorithms for computing tree edit distance between
unordered trees,
Theoretical Computer Science, 412, 352364, 2011.

J.B. Brown, T. Urata, T. Tamura, M. A. Arai, T. Kawabata and T. Akutsu,
Compound analysis via graph kernels incorporating chirality,
Journal of Bioinformatics and Computational Biology, 8,
Suppl. 1 (Suppl. for GIW 2010), 6381, 2010.

Y. Zhao, M. Hayashida and T. Akutsu,
Integer programmingbased method for grammarbased tree compression
and its application to pattern extraction of glycan tree structures,
BMC Bioinformatics, 11, Suppl. 11 (Suppl. for GIW 2010),
S4 (11 pages), 2010.

Y. Kato, K. Sato, M. Hamada, Y. Watanabe, K. Asai and T. Akutsu,
RactIP: fast and accurate prediction of RNARNA interaction
using integer programming,
Bioinformatics (Suppl. for ECCB 2010), 26, i460i466, 2010.

M. Hayashida and T. Akutsu,
Comparing biological networks via graph compression,
BMC Systems Biology, 4, Suppl. 2, S13 (11 pages), 2010.
Preliminary version has appeared in OSB 2009.

T. Akutsu,
A bisection algorithm for grammarbased compression of ordered trees,
Information Processing Letters, 110, 815820, 2010.

J. C. Nacher, M. Hayashida and T. Akutsu,
The role of internal duplication in the evolution of multidomain proteins,
BioSystems, 101, 127135, 2010.

T. Tamura and T. Akutsu,
Exact algorithms for finding a minimum reaction cut under a Boolean
model of metabolic networks,
IEICE Transactions on Fundamentals of Electronics,
Communications and Computer Sciences, E93A, 14971507, 2010.

A. A. Melkman, T. Tamura and T. Akutsu,
Determining a singleton attractor of an AND/OR Boolean network in
O(1.587^n) time,
Information Processing Letters, 110, 565569, 2010.

Y. Ishida, Y. Kato, L. Zhao, H. Nagamochi and T. Akutsu,
Branchandbound algorithms for enumerating treelike chemical
graphs with given path frequency using detachmentcut,
Journal of Chemical Information and Modeling, 50, 934946, 2010.

J. Song, K. Takemoto, H. Shen, H. Tan, M. M. Gromiha and
T. Akutsu,
Prediction of protein folding rates from structural
topology and complex network properties,
IPSJ Transactions on Bioinformatics, 3, 4053, 2010.

J. Song, H. Tan, H. Shen, K. Mahmood. S. E. Boyd, G. I. Webb,
T. Akutsu and J. C. Whisstock,
Cascleave: towards more accurate prediction of caspase substrate
cleavage sites,
Bioinformatics, 26, 752760, 2010.

T. Akutsu,
Tree edit distance problems: algorithms and applications to bioinformatics
(Invited Survey Paper),
IEICE Transactions on Information and Systems, E93D, 208218, 2010.

T. Tamura, K. Takemoto and T. Akutsu,
Finding minimum reaction cuts of metabolic networks under a Boolean model
using integer programming and feedback vertex sets,
International Journal of Knowledge Discovery in Bioinformatics,
1, 1431, 2010.
Preliminary version has appeared in IIBM 2009.

T. Akutsu, D. Fukagawa and A. Takasu,
Approximating tree edit distance through string edit distance,
Algorithmica, 57, 325348, 2010.
Preliminary version has appeared in ISAAC 2006.

M. Hayashida, T. Tamura, T. Akutsu, WK. Ching and Y. Cong,
Distribution and enumeration of attractors in probabilistic Boolean networks,
IET Systems Biology, 3, 465474, 2009.
Preliminary version has appeared in OSB 2008.

J. C. Nacher, T. Ochiai, M. Hayashida and T. Akutsu,
A mathematical model for generating bipartite graphs and its
application to protein networks,
Journal of Physics A: Mathematical and Theoretical,
42, 485005 (10pages), 2009.
Preliminary version has appeared in COMPLEX 2009.

J. Song, H. Tan, K. Mahmood, R. H. P. Law, A. M. Buckle, G. I. Webb, T. Akutsu and J. C. Whisstock,
Prodepth: predict residue depth by support vector regression approach from sequences only,
PLoS ONE, 4, e7072 (14 pages), 2009.

T. Akutsu and T. Tamura,
On finding a fixed point in a Boolean network with maximum indegree 2,
IEICE Transactions on Fundamentals of Electronics,
Communications and Computer Sciences, E92A, 17711778, 2009.

K. Mouri, J. C. Nacher and T. Akutsu,
A mathematical model for the detection mechanism of DNA doublestrand breaks
depending on autophosphorylation of ATM,
PLoS ONE, 4, e5131 (14 pages), 2009.

Y. Kato, T. Akutsu and H. Seki,
Dynamic programming algorithms and grammatical modeling for
protein betasheet prediction,
Journal of Computational Biology, 16, 945957, 2009.
Preliminary version has appeared in PRIB 2008.

T. Tamura and T. Akutsu,
Algorithms for singleton attractor detection in planar and
nonplanar AND/OR Boolean networks,
Mathematics in Computer Science, 2, 401420, 2009.
Preliminary version has appeared in AB 2008.

W.K. Ching, S.Q. Zhang, Y. Jiao, T. Akutsu, N.K. Tsing and A.S. Wong,
Optimal control policy for probabilistic Boolean networks
with hard constraints,
IET Systems Biology, 3, 9099, 2009.
Preliminary version has appeared in OSB 2007.

T. Tamura and T. Akutsu,
Detecting a singleton attractor in a Boolean
network utilizing SAT algorithms,
IEICE Transactions on Fundamentals of Electronics,
Communications and Computer Sciences,
E92A, 493501, 2009.
Preliminary version has appeared in FCT 2007.

U. Poolsap, Y. Kato and T. Akutsu,
Prediction of RNA secondary structure with pseudoknots
using integer programming,
BMC Bioinformatics, 10 (Supplement for APBC 2009),
S38 (11 pages), 2009.

Y. Kato, T. Akutsu and H. Seki,
A grammatical approach to RNARNA interaction prediction,
Pattern Recognition, 42, 531538, 2009.
Preliminary version has appeared in CMLS 2007.

J.C. Nacher, M. Hayashida and T. Akutsu,
Emergence of scalefree distribution in proteinprotein interaction networks
based on random selection of interacting domain pairs,
BioSystems, 95, 155159, 2009.

J. B. Brown and T. Akutsu,
Identification of novel DNA repair proteins via primary sequence, secondary structure, and homology,
BMC Bioinformatics, 10, 25, 2009.

T. Akutsu, M. Hayashida, SQ. Zhang, WK. Ching and M. K. Ng,
Analyses and algorithms for predecessor and control problems
for Boolean networks of bounded indegree,
IPSJ Transactions on Bioinformatics, 1, 2334, 2008.
Preliminary version has appeared in GENSIPS 2007.

T. Akutsu, D. Fukagawa and A. Takasu,
Improved approximation of the largest common subtree
of two unordered trees of bounded height,
Information Processing Letters, 109, 165170, 2008.

M. Hayashida, F. Sun, S. Aburatani, K. Horimoto and T. Akutsu,
Integer programmingbased approach to
allocation of reporter genes for cell array analysis,
International Journal of Bioinformatics Research and Applications,
4, 385399, 2008.
Preliminary version has appeared in OSB 2007.

K. Takemoto and T. Akutsu,
Origin of structural difference in metabolic networks with
respect to temperature,
BMC Systems Biology,
2, 82 (13 pages), 2008.

M. Hayashida, T. Tamura, T. Akutsu, SQ. Zhang and WK. Ching,
Algorithms and complexity analyses for control of singleton attractors
in Boolean networks,
EURASIP Journal on Bioinformatics and Systems Biology,
2008, 521407 (16pages), 2008.

H. Fujiwara, J. Wang, L. Zhao, H. Nagamochi and T. Akutsu,
Enumerating treelike chemical graphs with given path frequency,
Journal of Chemical Information and Modeling, 48, 13451357, 2008.

J. Song, H. Tan, K. Takemoto and T. Akutsu,
HSEpred: predict halfsphere exposure from protein sequences,
Bioinformatics, 24, 14891497, 2008.

M. Hayashida, T. Akutsu and H. Nagamochi,
A clustering method for analysis of sequence similarity networks of
proteins using maximal components of graphs,
IPSJ Transactions on Bioinformatics, 49Sig 5 (TBIO 4), 1524,
2008.
Preliminary version has appeared in APBC 2007.

T. Tamura and T. Akutsu,
Subcellular location prediction of proteins using support
vector machines with alignment of block sequences
utilizing amino acid composition,
BMC Bioinformatics, 8, 466, 2007.

K. Takemoto, J.C. Nacher and T. Akutsu,
Correlation between structure and temperature in prokaryotic metabolic networks,
BMC Bioinformatics, 8, 303, 2007.

J.C. Nacher and T. Akutsu,
Recent progress on the analysis of powerlaw features in complex
cellular networks (Review Paper),
Cell Biochemistry and Biophysics, 49 3747, 2007.

T. Ochiai, J.C. Nacher and T. Akutsu,
Emergence of the selfsimilar property in gene
expression dynamics,
Physica A, 382, 739752, 2007.

WK. Ching, SQ. Zhang, M.K. Ng and T. Akutsu,
An approximation method for solving the steadystate
probability distribution of probabilistic Boolean networks,
Bioinformatics, 23, 15111518, 2007.

K. Takemoto, C. Oosawa and T. Akutsu,
Structure of nclique networks embedded in a complex network,
Physica A, 380, 665672, 2007.

SQ. Zhang, M. Hayashida, T. Akutsu, WK. Ching and M. K. Ng,
Algorithms for finding small attractors in Boolean networks,
EURASIP Journal on Bioinformatics and Systems Biology,
2007, 20180 (13 pages), 2007.
 T. Tamura and T. Akutsu,
Approximation algorithms for optimal RNA secondary structures
common to multiple sequences,
IEICE Transactions on Fundamentals of Electronics,
Communications and Computer Sciences,
E90A, 917923, 2007.
 T. Akutsu, H. Bannai, S. Miyano and S. Ott,
On the complexity of deriving position specific score matrices
from positive and negative sequences,
Discrete Applied Mathematics, 155, 676685, 2007.
Preliminary version has appeared in CPM 2002.

T. Akutsu, H. Arimura and S. Shimozono,
Hardness results on local multiple alignment of biological sequences,
IPSJ Transactions on Bioinformatics, 48Sig 5 (TBIO 2), 3038,
2007.
Preliminary results have appeared in RECOMB 2000.
 T. Akutsu, M. Hayashida, WK. Ching and M.K. Ng,
Control of Boolean networks:
Hardness results and algorithms for tree structured networks,
Journal of Theoretical Biology, 244, 670679, 2007.
Preliminary version has appeared in APBC 2006.
 SQ. Zhang, WK. Ching, M.K. Ng and T. Akutsu,
Simulation study in Probabilistic Boolean Network models
for genetic regulatory networks,
International Journal of Data Mining and Bioinformatics,
1, 217240, 2007.
 J.C. Nacher and T. Akutsu,
Sensitivity of the powerlaw exponent in gene expression
distribution to mRNA decay rate,
Physics Letters A, 360, 174178, 2006.
 T. Akutsu,
A relation between edit distance for ordered trees and
edit distance for Euler strings,
Information Processing Letters, 100, 105109, 2006.
 M.K. Ng, SQ. Zhang, WK. Ching and T. Akutsu,
A control model for Markovian genetic regulatory networks,
Transactions on Computational Systems Biology V
(Lecture Notes in Bioinformatics 4070), 3648, 2006.
 J.C. Nacher, JM. Schwartz, M. Kanehisa and T. Akutsu,
Identification of metabolic units induced by environmental signals,
Bioinformatics (Proc. ISMB 2006), 22, e375e383, 2006.
 T. Akutsu,
Algorithms for point set matching with kdifferences,
International Journal of Foundations of Computer Science,
17, 903917, 2006.
Preliminary version has appeared in COCOON 2004.
 D. Fukagawa and T. Akutsu,
Fast algorithms for comparison of similar unordered trees,
International Journal of Foundations of Computer Science,
17, 703729, 2006.
Preliminary version has appeared in ISAAC 2004.
 J.C. Nacher, M. Hayashida and T. Akutsu,
Protein domain networks: Scalefree mixing of positive and
negative exponents,
Physica A, 367, 538552, 2006.
 H. Saigo, JP. Vert and T. Akutsu,
Optimizing amino acid substitution matrices with a local alignment
kernel,
BMC Bioinformatics, 7, 246, 2006.
 T. Akutsu,
Recent advances in RNA secondary structure prediction with
pseudoknots (Review Paper),
Current Bioinformatics, 1, 115129, 2006.

Dukka Bahadur K.C., E. Tomita, J. Suzuki, K. Horimoto and T. Akutsu,
Protein threading with profiles and distance constraints
using clique based algorithms,
Journal of Bioinformatics and Computational Biology,
4, 1942, 2006.
Preliminary version has appeared in APBC 2005.
 T. Akutsu, M. Hayashida, Dukka Bahadur K.C., E. Tomita, J. Suzuki
and K. Horimoto,
Dynamic programming and clique based approaches for protein threading
with profiles and constraints,
IEICE Transactions on
Fundamentals of Electronics, Communications and Computer Sciences,
E89A, 12151222, 2006.
Preliminary version has appeared in BIBE 2004.

J.C. Nacher, T. Ochiai, T. Yamada, M. Kanehisa and T. Akutsu,
The role of lognormal dynamics in the evolution of biochemical pathways,
BioSystems, 83, 2637, 2006.
 S. Matsuda, JP. Vert, H. Saigo, N. Ueda, H. Toh and T. Akutsu,
A novel representation of protein sequences for prediction of
subcellular location using support vector machines,
Protein Science, 14, 28042813, 2005.

J.C. Nacher, T. Ochiai and T. Akutsu,
On the relation between fluctuations and scalinglaw
in gene expression time series from yeast to human,
Modern Physics Letters B, 19, 11691177, 2005.

WK. Ching, M.K. Ng, E.S. Fung and T. Akutsu,
On construction of stochastic genetic networks based on
gene expression sequences,
International Journal of Neural Systems,
15, 297310, 2005.

P. Mahe, N. Ueda, T. Akutsu, JL. Perret and JP. Vert,
Graph kernels for molecular structureactivity relationship
analysis with support vector machines,
Journal of Chemical Information and Modeling, 45,
939951, 2005.
Preliminary version has appeared in ICML 2004.

T. Ochiai, J.C. Nacher and T. Akutsu,
A stochastic approach to multigene expression dynamics,
Physics Letters A, 339, 19, 2005.

N. Ueda, K.F. AokiKinoshita, A. Yamaguchi, T. Akutsu and
H. Mamitsuka,
A probabilistic model for mining labeled ordered trees:
capturing patterns in carbohydrate sugar chains,
IEEE Transactions on Knowledge and Data Engineering,
17, 10511064, 2005.

K.F. Aoki, H. Mamitsuka, T. Akutsu and M. Kanehisa,
A score matrix to reveal the hidden links in glycans,
Bioinformatics, 21, 14571463, 2005.

J.C. Nacher, N. Ueda, M. Kanehisa and T. Akutsu,
Flexible construction of hierarchical scalefree networks with
general exponent,
Physical Review E, 71, 036132(17), 2005.

M. Itoh, S. Goto, T. Akutsu and M. Kanehisa,
Fast and accurate database homology search using upper bounds of
local alignment scores,
Bioinformatics, 21, 912921, 2005.

Dukka Bahadur K.C., E. Tomita, J. Suzuki and T. Akutsu,
Protein sidechain packing problem: a maximum edgeweight
clique algorithmic approach,
Journal of Bioinformatics and Computational Biology,
3, 103126, 2005.
Preliminary version has appeared in APBC 2004.

J.C. Nacher, T. Yamada, S. Goto, M. Kanehisa and T. Akutsu,
Two complementary representations of a scalefree network,
Physica A, 349, 349363, 2005.

M. Hayashida, N. Ueda and T. Akutsu,
A fast method for inferring strengths of proteinprotein interactions
and a hardness result,
The IEICE Transactions on Fundamentals of Electronics, Communications and
Computer Sciences (Japanese Edition), J88A, 8390, 2005.
Preliminary version has appeared in IBSB 2004.

D. Fukagawa and T. Akutsu,
Performance analysis of a greedy algorithm for inferring Boolean functions,
Information Processing Letters, 93, 712, 2005.
Preliminary version has appeared in DS 2003.

J.C. Nacher, N. Ueda, T. Yamada, M. Kanehisa and T. Akutsu,
Clustering under the line graph transformation:
application to reaction network,
BMC Bioinformatics, 5, 207, 2004.

T. Ochiai, J.C. Nacher and T. Akutsu,
A constructive approach to gene expression dynamics,
Physics Letters A, 330, 313321, 2004.

K.F. Aoki, N. Ueda, A. Yamaguchi, M. Kanehisa, T. Akutsu and H. Mamitsuka,
Application of a new probabilistic model for recognizing complex patterns
in glycans,
Bioinformatics, 20, Suppl. 1 (Proc. ISMB/ECCB 2004),
i6i14, 2004.

K.F. Aoki, A. Yamaguchi, N. Ueda, T. Akutsu,
H. Mamitsuka, S. Goto and M. Kanehisa,
KCaM (KEGG Carbohydrate Matcher): a software tool for
analyzing the structures of carbohydrate sugar chains,
Nucleic Acids Research, 32, Web Server Issue, w267w272, 2004.

H. Saigo, JP. Vert, N. Ueda and T. Akutsu,
Protein homology detection using string alignment kernels,
Bioinformatics, 20, 16821689, 2004.

K.F. Aoki, N. Ueda, A. Yamaguchi, T. Akutsu, M. Kanehisa and H. Mamitsuka,
Managing and analyzing carbohydrate data,
ACM SIGMOD Record (Magazine), 33, 2004.

T. Akutsu,
Efficient extraction of mapping rules of atoms from
enzymatic reaction data,
Journal of Computational Biology, 11, 449462, 2004.
Preliminary version has appeared in RECOMB 2003.

Y. Hourai, T. Akutsu and Y. Akiyama,
Optimizing substitution matrices by separating score
distributions,
Bioinformatics, 20, 863873, 2004.

M. Hayashida, N. Ueda and T. Akutsu,
Inferring strengths of proteinprotein interactions
from experimental data using linear programming,
Bioinformatics, 19, ii58ii65, 2003.

D. Shinozaki, T. Akutsu and O. Maruyama,
Finding optimal degenerated patterns in DNA sequences,
Bioinformatics, 19, ii206ii214, 2003.

T. Akutsu, S. Kuhara, O. Maruyama and S. Miyano,
Identification of genetic networks by strategic gene disruptions and
gene overexpressions under a boolean model,
Theoretical Computer Science, 298, 235251, 2003.
Preliminary version has appeared in SODA'98.

T. Akutsu, K. Kanaya, A. Ohyama and A. Fujiyama,
Point matching under nonuniform distortions,
Discrete Applied Mathematics, 127, 521, 2003.
Preliminary version has appeared in CPM'99.

T. Akutsu, S. Miyano and S. Kuhara,
A simple greedy algorithm for finding functional relations:
efficient implementation and average case analysis,
Theoretical Computer Science, 292, 481495, 2003.
Preliminary version has appeared in DS 2000.

T. Akutsu, S. Miyano and S. Kuhara,
Algorithms for identifying Boolean networks and related biological networks
based on matrix multiplication and fingerprint function,
Journal of Computational Biology, 7, 331343, 2000.

T. Akutsu, S. Miyano and S. Kuhara,
Inferring qualitative relations in genetic networks
and metabolic pathways,
Bioinformatics, 16, 727734, 2000.

T. Akutsu,
Dynamic programming algorithms for RNA secondary structure prediction
with pseudoknots,
Discrete Applied Mathematics, 104, 4562, 2000.

T. Akutsu and M. M. Halldorsson,
On the approximation of largest common subtrees and largest common point
sets,
Theoretical Computer Science, 233, 3350, 2000.
Preliminary version has appeared in ISAAC'94.

T. Akutsu,
Approximation and exact algorithms for RNA secondary structure
prediction and recognition of stochastic contextfree languages,
Journal of Combinatorial Optimization, 3, 321336, 1999.
Preliminary version has appeared in ISAAC'98.

T. Akutsu and S. Miyano,
On the approximation of protein threading,
Theoretical Computer Science 210, 261275, 1999.
Preliminary version has appeared in RECOMB '97.

T. Akutsu, H. Tamaki and T. Tokuyama,
Distribution of distances and triangles in a point set and algorithms
for computing the largest common point sets,
Discrete and Computational Geometry, 20, 307331, 1998.
Preliminary version has appeared in ACM Symp. Computational Geometry.

T. Akutsu,
On determining the congruence of point sets in d dimensions,
Computational Geometry: Theory and Applications, 9, 247256, 1998.
Preliminary version has appeared as
On determining the congruity of point sets in higher dimensions in ISAAC'94.

T. Akutsu, K. Onizuka and M. Ishikawa,
Rapid protein fragment search using hash functions based on
the Fourier transform (Short Paper),
Computer Applications in the Biosciences (CABIOS) 13, 357364, 1997.
Preliminary version has appeared in HICSS28.

T. Akutsu,
Protein structure alignment
using dynamic programming and iterative improvement,
IEICE Trans. Information and Systems E79D, 16291636, 1996.

T. Akutsu,
Approximate string matching
with variable length don't care characters,
IEICE Trans. Information and Systems E79D, 13531354, 1996 (LETTER).

T. Akutsu,
Approximate string matching with don't care characters,
Information Processing Letters 55, 235239, 1995.
Preliminary version has appeared in CPM'94.

T. Akutsu,
A parallel algorithm for determining the congruence of point sets in threedimensions,
IEICE Trans. Information and Systems E78D, 321325, 1995.

T. Akutsu and A. Takasu,
On PAC learnability of functional dependencies,
New Generation Computing 12, 359374, 1994.
Preliminary version has appeared in ALT'92.

T. Akutsu,
A linear time pattern matching algorithm between a string and a tree,
IEICE Trans. Information and Systems E77D, 281287, 1994.
Preliminary version has appeared in CPM'93.

T. Akutsu,
A polynomial time algorithm for finding a largest common subgraph of almost
trees of bounded degree,
IEICE Trans. Fundamentals, E76A, 14881493, 1993.

T. Akutsu, S.Kobayashi, K.Hori and S.Ohsuga,
Algorithms for finding the largest subtree whose copies cover all the
leaves,
IEICE Trans. Information and Systems, E76D, 707710, 1993 (LETTER).

A. Takasu and T. Akutsu,
A minimum path decomposition of the Hasse diagram for testing the
consistency of functional dependencies,
IEICE Trans. Information and Systems, E76D, 299301, 1993 (LETTER).

E. Suzuki, T. Akutsu and S. Ohsuga,
Knowledgebased system for computeraided drug design,
KnowledgeBased Systems, 6, 114126, 1993.

T. Akutsu,
An RNC algorithm for finding a largest common subtree of two trees,
IEICE Trans. Information and Systems, E75D, 95101, 1992.

T.Akutsu,
An NC algorithm for computing canonical forms of graphs of bounded
separator,
IEICE Trans. Fundamentals, E75A, 512514, 1992 (LETTER).

T. Akutsu,
An $O(n^2)$ time algorithm for computing a canonical form of a chemical
structure which has a planar graph structure,
Transactions of Information Processing Society of Japan, 33, 14871496,
1992 (in Japanese).

T. Akutsu,
A new method of computer representation of stereochemistry.
Transforming a stereochemical structure into a graph,
Journal of Chemical Information and Computer Sciences, 31, 414417, 1991.

T. Akutsu, E. Suzuki and S. Ohsuga,
Logicbased approach to expert systems in chemistry,
KnowledgeBased Systems, 4, 103116, 1991.

T. Akutsu, C. Li, E. Suzuki and S. Ohsuga,
Development of a tool for building expert systems in organic chemistry,
Transactions of Information Processing Society of Japan, 32, 425434,
1991 (in Japanese).

T. Akutsu and S. Ohsuga,
Some properties of Prolog,
Journal of Japanese Society for Artificial Intelligence, 2, 223233,
1987 (in Japanese).
Conference Papers

T. Akutsu, T. Mori, N. Nakamura, S. Kozawa, Y. Ueno, and T. N. Sato,
On the complexity of tree edit distance with variables,
Proc. 33rd International Symposium on Algorithms and Computation (ISAAC 2022),
44 (14 pages), 2022.

J. Zhu, K. Haraguchi, H. Nagamochi, and T. Akutsu,
Adjustive linear regression and its application to the inverse QSAR (short paper),
Proc. 15th International Joint Conference on Biomedical Engineering Systems
and Technologies (BIOSTEC 2022), 144151, 2022.

J. Zhu, N. A. Azam, K. Haraguchi, L. Zhao, H. Nagamochi, and T. Akutsu,
A method for molecular design based on linear regression and
integer programming,
Proc. 12th International Conference on Bioscience
Biochemistry and Bioinformatics (ICBBB '22), 8 pages, 2022.

N. A. Azam, J. Zhu, K. Haraguchi, L. Zhao, H. Nagamochi, and T. Akutsu,
Molecular design based on artificial neural networks, integer programming
and grid neighbor search (short paper),
Proc. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2021),
360363, 2021.

K. Tanaka, J. Zhu, N. A. Azam, K. Haraguchi, L. Zhao, H. Nagamochi, and T. Akutsu,
An inverse QSAR method based on decision tree and integer programming,
Proc. 17h International Conference on Intelligent Computing (ICIC 2021),
Lecture Notes in Computer Science 12837, 628644, 2021.

J. Zhu, N. A. Azam, K. Haraguchi, L. Zhao, H. Nagamochi, and T. Akutsu,
An improved integer programming formulation for inferring chemical compounds
with prescribed topological structures,
Proc. 34th International Conference on Industrial, Engineering and
Other Applications of Applied Intelligent Systems (IEA/AIE 2021),
197209, 2021.

R. Ito, N. A. Azam, C. Wang, A. Shurbevski, H. Nagamochi, and T. Akutsu,
A novel method for the inverse QSAR/QSPR to monocyclic chemical
compounds based on artificial neural networks and integer programming,
Proc. 21st International Conference on Bioinformatics &
Computational Biology, 2020.

F. Zhang, J. Zhu, R. Chiewvanichakorn, A. Shurbevski, H. Nagamochi, and T. Akutsu,
A new integer linear programming formulation to the inverse QSAR/QSPR for acyclic chemical compounds using skeleton trees,
Proc. 33rd International Conference on Industrial, Engineering and
Other Applications of Applied Intelligent Systems (IEA/AIE 2020),
Lecture Notes in Computer Science 12144, 433444, 2020.

R. Chiewvanichakorn, C. Wang, Z. Zhang, A. Shurbevski, H. Nagamochi, and T. Akutsu,
A method for the inverse QSAR/QSPR based on artificial neural networks and
mixed integer linear programming,
Proc. 2020 10th International Conference on Bioscience, Biochemistry and Bioinformatics (ICBBB 2020), 4046, 2020.

J. Zeng, H. Cai, and T. Akutsu,
Breast cancer subtype by imbalanced omics data through a deep learning fusion model,
Proc. 2020 10th International Conference on Bioscience, Biochemistry and Bioinformatics (ICBBB 2020), 7883, 2020.

N. A. Azam, R. Chiewvanichakorn, F. Zhang, A. Shurbevski, H. Nagamochi, and
T. Akutsu,
A novel method for the inverse QSAR/QSPR based on artificial neural
networks and mixed integer linear programming with guaranteed
admissibility (short paper),
Proc. 13th International Joint Conference on Biomedical Engineering Systems
and Technologies (BIOSTEC 2020), 101108, 2020.

T. Akutsu and H. Nagamochi,
A mixed integer linear programming formulation to artificial neural networks,
Proc. 2nd International Conference on Information Science and System (ICISS 2019), 215220, 2019.

T. Akutsu, J. Jansson, R. Li, A. Takasu and T. Tamura,
New and improved algorithms for unordered tree inclusion,
Proc. 29th International Symposium on Algorithms and Computation (ISAAC 2018),
27:127:12, 2018.

T. Matsubara, J. C. Nacher, T. Ochiai, M. Hayashida and T, Akutsu,
Convolutional neural network approach to lung cancer classification
integrating protein interaction network and gene expression profiles
(short paper),
International Workshop on Cancer Bioinformatics and Intelligent Medicine 2018
(CBIM 2018),
in Proc. 18th IEEE International Conference on BioInformatics
and BioEngineering (BIBE 2018),
151154, 2018.

CY, Lin, R. Li, T. Akutsu, P. Ruan, S. Sea and JM. Yang,
Deep learning with evolutionary and genomic profiles for identifying cancer subtypes (short paper),
International Workshop on Cancer Bioinformatics and Intelligent Medicine 2018
(CBIM 2018),
in Proc. 18th IEEE International Conference on BioInformatics
and BioEngineering (BIBE 2018),
147150, 2018.

T. Akutsu, C. de la Higuera and T. Tamura,
A simple lineartime algorithm for computing the centroid and canonical form of a plane graph and its applications,
Proc. 29th Annual Symposium on Combinatorial Pattern Matching (CPM 2018),
10:110:12, 2018.

Y. Tamura, A. Shurbevski, H. Nagamochi and T. Akutsu,
Enumerating chemical monoblock 3augmented trees with two junctions,
Proc. 8th International Conference on Bioscience, Biochemistry and
Bioinformatics (ICBBB 2018), 4855, 2018.

M. Hayashida, H. Koyano and T. Akutsu,
Grammarbased compression for directed and undirected generalized
seriesparallel graphs using integer linear programming (short paper),
Proc. 11th International Joint Conference on Biomedical Engineering Systems
and Technologies (BIOSTEC 2018)  Volume 3: BIOINFORMATICS,
105111, 2018.

J. Jindalertudomdee, M. Hayashida, J. Song and T. Akutsu,
Hostpathogen protein interaction prediction based on local topology
structures of a protein interaction network,
Proc. IEEE 16th International Conference on Bioinformatics and
Bioengineering (BIBE 2016), 712, 2016.

T. Tamura, CY. Lin, JM. Yang and T. Akutsu,
Finding influential genes using gene expression data and
Boolean models of metabolic networks,
Proc. IEEE 16th International Conference on Bioinformatics and
Bioengineering (BIBE 2016), 5763, 2016.

F. He, A. Hanai, H. Nagamochi and T. Akutsu,
Enumerating naphthalene isomers of treelike chemical graphs (Short Paper),
Proc. 9th International Joint Conference on Biomedical Engineering Systems
and Technologies (BIOSTEC 2016)  Volume 3: BIOINFORMATICS,
258265, 2016.

Y. Qiu, X. Cheng, WK. Ching, H. Jiang, T. Akutsu,
On observability of attractors in Boolean networks (short paper),
Proc. 2015 IEEE International Conference on Bioinformatics and Biomedicine
(BIBM 2015), 263266, 2015.

T. Akutsu, J. Jansson, A. Takasu and T. Tamura,
On the parameterized complexity of associative and commutative unification,
Post Proc. 9th International Symposium on Parameterized and Exact Computation (IPEC 2014),
Lecture Notes in Computer Science 8894, 1527, 2014.

M. Hayashida, H. Koyano and T. Akutsu,
Measuring the similarity of protein structures using image local feature
descriptors SIFT and SURF,
Proc. 8th International Conference on Systems Biology and
4th Translational Bioinformatics Conference (ISB/TBC 2014),
167171, 2014.

J.C. Nacher and T. Akutsu,
Analysis on critical nodes in controlling complex networks
using dominating sets,
Second Workshop on Complex Networks and their Applications,
(A Part of Proc. 2013 Int. Conf. SignalImage Technology &
InternetBased Systems (SITIS 2013)), 649654, 2013.

T. Akutsu, T. Tamura, A. A. Melkman and A. Takasu,
On the complexity of finding a largest common subtree of
bounded degree,
Proc. 19th Int. Symp. Fundamentals of Computation Theory (FCT 2013),
Lecture Notes in Computer Science 8070, 415, 2013.

Y. Sakuma, M. Kamada, M. Hayashida and T. Akutsu,
Inferring strengths of proteinprotein interactions
using support vector regression,
Proc. 2013 International Conference on Parallel and Distributed
Processing Techniques and Applications (PDPTA2013), 2013.

N. Nakajima and T. Akutsu,
Network completion for time varying genetic networks,
The 6th International Workshop on Intelligent Informatics in Biology and Medicine
(IIBM 2013),
(A Part of Proc. 7th International Conference
on Complex, Intelligent and Software Intensive Systems (CISIS2013)),
553558, 2013.
 J. C. Nacher and T. Akutsu,
Analysis on controlling complex networks based on dominating sets,
Journal of Physics: Conference Series 410, 012104, 2013.
(ICMSQUARE 2012: International Conference on Mathematical Modelling in Physical Sciences)

T. Akutsu and T. Tamura,
On the complexity of the maximum common subgraph problem for
partial ktrees of bounded degree,
Proc. 23rd International Symposium on Algorithms and Computation (ISAAC 2012),
Lecture Notes in Computer Science 7676, 146155, 2012.

T. Akutsu, M. Hayashida and T. Tamura,
Finding conserved regions in protein structures using support vecto
rmachines and structure alignment,
Proc. 7th IAPR International Conference on Pattern Recognition
in Bioinformatics (PRIB2012),
Lecture Notes in Bioinformatics 7632, 233242, 2012.

T. Akutsu and T. Tamura,
A polynomialtime algorithm for computing the maximum common subgraph
of outerplanar graphs of bounded degree,
Proc. 37th International Symposium on Mathematical Foundations of
Computer Science (MFCS 2012),
Lecture Notes in Computer Science 7464, 7687, 2012.

M. Hayashida, M. Kamada, J. Song and T. Akutsu,
Predicting proteinRNA residuebase contacts using twodimensional conditional random field,
Proc. 6th IEEE International Conference on Systems Biology (ISB 2012), 152157, 2012.

T. Akutsu, T. Tamura, D. Fukagawa and A. Takasu,
Efficient exponential time algorithms for edit distance between unordered trees,
Proc. 23rd Annual Symposium on Combinatorial Pattern Matching (CPM 2012),
Lecture Notes in Computer Science 7354, 360372, 2012.

M. Kamada, M. Hayashida, J. Song and T. Akutsu,
Discriminative random field approach to prediction of protein residue contacts,
Proc. 5th IEEE International Conference on Systems Biology (ISB 2011), 285291, 2011.

M. Wang, HB. Shen, T. Akutsu and J. Song,
Predicting functional impact of single amino acid polymorphisms by integrating
sequence and structural features.
Proc. 5th IEEE International Conference on Systems Biology (ISB 2011), 1826, 2011.

T. Akutsu, T. Mori, T. Tamura, D. Fukagawa, A. Takasu and E. Tomita,
An improved cliquebased method for computing edit distance between
unordered trees and its application to comparison of glycan structures,
The 4th International Workshop on Intelligent Informatics in Biology and Medicine
(IIBM 2011),
A Part of Proc. 5th International Conference
on Complex, Intelligent and Software Intensive Systems, 536540, 2011.

X. Chen, T. Akutsu, T. Tamura and WK. Ching,
Finding optimal control policy in probabilistic Boolean networks with hard constraints by using integer programming and dynamic programming,
Proc. IEEE International Conference on Bioinformatics and Biomedicine 2010 (BIBM 2010),
240246, 2010.

M. Hayashida, P. Ruan and T. Akutsu,
A quadsection algorithm for grammarbased image compression,
Proc. 2nd Int. Conf. Future Generation Information Technology 2010 (FGIT 2010),
Lecture Notes in Computer Science 6485, 234248, 2010.

M. Hayashida, M. Kamada, J. Song and T. Akutsu,
Conditional random field approach to prediction of proteinprotein
interactions using mutual information between domains,
Proc. 4th International Conference on Computational Systems Biology (ISB2010),
Lecture Notes in Operations Research 13, 276284, 2010.

A. Takasu, D. Fukagawa and T. Akutsu,
A variational Bayesian EM algorithm for tree similarity,
Proc. 20th International Conference on Pattern Recognition (ICPR 2010),
10561059, 2010.

T. Tamura, Y. Yamanishi, M. Tanabe, S. Goto, M. Kanehisa, K. Horimoto
and T. Akutsu,
Integer programmingbased method for completing signaling pathways
and its application to analysis of colorectal cancer,
Genome Informatics, 24
(The 10th Int. Workshop on Bioinformatics and Systems Biology),
193203, 2010.

Y. Zhao, T. Tamura, M. Hayashida and T. Akutsu,
A dynamic programming algorithm to predict synthesis processes of
treestructured compounds with graph grammar,
Genome Informatics, 24
(The 10th Int. Workshop on Bioinformatics and Systems Biology),
218229, 2010.

U. Poolsap, Y. Kato and T. Akutsu,
Dynamic programming algorithms for RNA structure prediction
with binding sites,
Proc. Pacific Symposium on Biocomputing 2010 (PSB 2010), 98107, 2010.

T. Akutsu, M. Hayashida and T. Tamura,
Integer programmingbased methods for attractor
detection and control of Boolean networks,
Proc. The combined 48th IEEE Conference on Decision and Control
and 28th Chinese Control Conference (IEEE CDC/CCC 2009), 56105617, 2009.

T. Imada, S. Ota, H. Nagamochi and T. Akutsu,
Enumerating stereoisomers of tree structured molecules using dynamic programming,
Proc. 20th International Symposium on Algorithms and Computation (ISAAC 2009),
Lecture Notes in Computer Science 5878, 1423, 2009.

T. Tamura, N. Christian, K. Takemoto, O. Ebenhoeh and T. Akutsu,
Analysis and prediction of nutritional requirements using structural
properties of metabolic networks and support vector machines,
Genome Informatics,
22 (The 9th Int. Workshop on Bioinformatics and Systems Biology),
176190, 2009.

Y. Cong, T. Tamura, T. Akutsu and WK. Ching,
Efficient computation of impact degrees for multiple reactions in metabolic
networks with cycles (short paper),
Proc. ACM Third International Workshop on Data and Text Mining in
Bioinformatics (DTMBIO 2009), 6770, 2009.

A. Takasu, D. Fukagawa and T. Akutsu,
Latent topic extraction from relational table for record matching
(regular paper),
Proc. 12th International Conference on Discovery Science (DS 2009),
Lecture Notes in Artificial Intelligence 5808, 449456, 2009.

T. Akutsu, T. Tamura and K. Horimoto,
Completing networks using observed data,
Proc. 20th International Conference on
Algorithmic Learning Theory (ALT 2009),
Lecture Notes in Artificial Intelligence 5809, 126140, 2009.

M. Hayashida and T. Akutsu,
Comparing biological networks via graph compression,
Proc. 3rd International Symposium on Optimization and Systems Biology
(OSB 2009),
Lecture Notes in Operations Research 11, 168176, 2009.

D. Fukagawa, T. Akutsu and A. Takasu,
Constant factor approximation of edit distance of bounded height
unordered trees,
Proc. 16th International Symposium on String Processing and
Information Retrieval (SPIRE 2009),
Lecture Notes in Computer Science 5721, 717, 2009.

T. Tamura, K. Takemoto and T. Akutsu,
Measuring structural robustness of metabolic networks
under a Boolean model using integer programming and feedback vertex sets,
The 2nd International Workshop on Intelligent Informatics
in Biology and Medicine (IIBM 2009),
A Part of Proc. 3rd International Conference
on Complex, Intelligent and Software Intensive Systems,
819824, 2009.

J. C. Nacher, T. Ochiai, M. Hayashida and T. Akutsu,
A bipartite graph based model of protein domain networks,
Proc. 1st International Conference on Complex Sciences:
Theory and Applications (Complex 2009), Part1,
Lecture Notes of the Institute for Computer Sciences,
Social Informatics and Telecommunications Engineering 4,
525535, 2009.

Y. Ishida, L. Zhao, H. Nagamochi and T. Akutsu,
Improved algorithms for enumerating treelike chemical
graphs with given path frequency,
Genome Informatics, 21
(The 19th Int. Conference on Genome Informatics),
5364, 2008.

M. Hayashida, T. Tamura, T. Akutsu and WK. Ching,
On distribution and enumeration of attractors
in probabilistic Boolean networks,
Proc. 2nd International Symposium on Optimization and
Systems Biology (OSB 2008),
Lecture Notes in Operations Research 9,
91100, 2008.

Y. Kato, T. Akutsu and H. Seki,
Prediction of protein betasheets: dynamic programming versus
grammatical approach,
Proc. 3rd IAPR International Conference on
Pattern Recognition in Bioinformatics (PRIB 2008),
Lecture Notes in Bioinformatics 5265, 6677, 2008.

T. Akutsu, M. Hayashida and T. Tamura,
Algorithms for inference, analysis and control of Boolean networks
(nonrefereed tutorial paper),
Proc. 3rd International Conference on Algebraic Biology (AB 2008),
Lecture Notes in Computer Science 5147, 115, 2008.

T. Tamura and T. Akutsu,
An improved algorithm for detecting a singleton attractor
in a Boolean network consisting of AND/OR nodes,
Proc. 3rd International Conference on Algebraic Biology (AB 2008),
Lecture Notes in Computer Science 5147, 216229, 2008.

M. Hayashida and T. Akutsu,
Image compressionbased approach to measuring
the similarity of protein structures,
Proc. 6th AsiaPacific Bioinformatics Conference (APBC 2008),
221230, 2008.

Y. Kato, T. Akutsu and H. Seki,
A grammatical approach to RNARNA interaction prediction,
Proc. 2007 International Symposium on
Computational Models for Life Sciences (CMLS 2007),
197206. 2007.

A. Takasu, D. Fukagawa and T. Akutsu,
Statistical learning algorithm for tree similarity (short paper),
Proc. the Seventh IEEE International Conference on Data Mining (ICDM 2007),
667672, 2007.

T. Tamura and T. Akutsu,
An O(1.787^n)time algorithm for detecting a singleton attractor
in a Boolean network consisting of AND/OR nodes,
Proc. 16th International Symposium on Fundamentals of Computation
Theory (FCT 2007),
Lecture Notes in Computer Science 4639, 494505, 2007.

M. Hayshida, F. Sun, S. Aburatani, K. Horimoto and T. Akutsu,
Integer programmingbased approach to allocation of reporter
genes for cell array analysis,
Proc. International Symposium on Optimization and
Systems Biology (OSB 2007),
Lecture Notes in Operations Research 7,
2128, 2007.

WK. Ching, SQ. Zhang, Y. Jiao, T. Akutsu and A.S. Wong,
Optimal finitehorizon control for probabilistic Boolean
networks with hard constraints,
Proc. International Symposium on Optimization and
Systems Biology (OSB 2007),
Lecture Notes in Operations Research 7,
288301, 2007.

T. Akutsu, M. Hayashida, SQ. Zhang, WK. Ching and M. K. Ng,
Finding incoming global states in Boolean networks,
Proc. 5th IEEE International Workshop on Genomic Signal
Processing and Statistics (GENSIPS07)
(appeared as a peer reviewed poster paper).

J. Wang, L. Zhao, H. Nagamochi and T. Akutsu,
An efficient algorithm for generating colored outerplanar graphs,
Proc. 4th Annual Conference on Theory and Applications
of Models of Computation (TAMC07),
Lecture Notes in Computer Science 4484, 573583, 2007.

J.C. Nacher, M. Hayashida and T. Akutsu,
Topological aspects of protein networks,
PostProc. Workshop on Emergent Intelligence on Networked Agents (WEIN06),
Studies in Computational Intelligence 56, 147158, 2007.

T. Akutsu and D. Fukagawa,
Inferring a chemical structure from a feature vector
based on frequency of labeled paths and small fragments,
Proc. 5th AsiaPacific Bioinformatics Conference (APBC 2007),
165174, 2007.

M. Hayashida, T. Akutsu and H. Nagamochi,
A novel clustering method for analysis of biological networks
using maximal components of graphs,
Proc. 5th AsiaPacific Bioinformatics Conference (APBC 2007),
257266, 2007.

T. Akutsu, D. Fukagawa and A. Takasu,
Approximating tree edit distance through string edit distance,
Proc. 17th International Symposium on Algorithms and Computation
(ISAAC 2006),
Lecture Notes in Computer Science 4288, 9099, 2006.

J.B. Brown, Dukka Bahadur K. C., E. Tomita and T. Akutsu,
Multiple methods for protein side chain packing using
maximum weight cliques,
Genome Informatics, 171
(The 6th Int. Workshop on Bioinformatics and Systems Biology),
312, 2006.

T. Akutsu and J.C. Nacher,
Theoretical and computational analyses of structures of
metabolic networks and proteinprotein interaction networks
(invited nonrefereed paper),
The First International Conference on
Computational Systems Biology, 2006.

T. Akutsu, M. Hayashida, WK. Ching and M.K. Ng,
On the complexity of finding control strategies for boolean networks,
Proc. 4th AsiaPacific Bioinformatics Conference (APBC 2006),
99108, 2006.

T. Akutsu and D. Fukagawa,
On inference of a chemical structure from path frequency,
Proc. 2005 International Joint Conference of InCoB, AASBi and KSBI
(BIOINFO2005), 96100, 2005.

Dukka Bahadur K.C., J.B. Brown, E. Tomita, J. Suzuki and T. Akutsu,
Large scale protein sidechain packing based on maximum edgeweight
clique finding algorithm,
Proc. 2005 International Joint Conference of InCoB, AASBi and KSBI
(BIOINFO2005), 228233, 2005.

L.M.C. Meireles and T. Akutsu,
A gibbs sampling approach to detection of tree motifs,
Genome Informatics, 161
(The 5th Int. Workshop on Bioinformatics and Systems Biology),
3443, 2005.

H.A. Moesa, Dukka Bahadur K.C. and Tatsuya Akutsu,
Efficient determination of cluster boundaries for analysis of
gene expression profile data using hierarchical clustering and
wavelet transform,
Genome Informatics, 161
(The 5th Int. Workshop on Bioinformatics and Systems Biology),
132141, 2005.

SQ. Zhang, M.K. Ng, WK. Ching and T. Akutsu,
A linear control model for gene intervention in a genetic regulatory
network,
Proc. IEEE International Conference on Granular Computing (GrC 2005),
354358, 2005.

T. Akutsu and D. Fukagawa,
Inferring a graph from path frequency,
Proc. 16th Annual Symposium on Combinatorial Pattern Matching (CPM 2005),
Lecture Notes in Computer Science 3537, 371382, 2005.

T. Akutsu,
Computational and statistical methods in bioinformatics
(nonrefereed tutorial paper),
PostProceedings AM2003,
Lecture Notes in Computer Science 3430, 1133, 2005.

Dukka Bahadur K.C., E. Tomita, J. Suzuki, K. Horimoto and
T. Akutsu,
Clique based algorithms for protein threading with
profiles and constraints,
Proc. 3rd AsiaPacific Bioinformatics Conference (APBC 2005),
5164, 2005.

D. Fukagawa and T. Akutsu,
Fast algorithms for comparison of similar unordered trees,
Proc. 15th Int Symp. Algorithms and Computation (ISAAC 2004),
Lecture Notes in Computer Science 3341, 452463, 2004.

T. Akutsu,
Algorithms for point set matching with kdifferences,
Proc. 10th Int. Computing and Combinatorics Conference
(COCOON 2004),
Lecture Notes in Computer Science 3106, 249258, 2004.

P. Mahe, N. Ueda, T. Akutsu, JL. Perret and JP. Vert,
Extensions of marginalized graph kernels,
Proc. 21st Int. Conf. Machine Learning (ICML 2004), 552559, 2004.

M. Hayashida, N. Ueda and T. Akutsu,
A simple method for inferring strengths of proteinprotein
interactions,
Genome Informatics, 151
(The 4th Int. Workshop on Bioinformatics and Systems Biology),
5668, 2004.

M. Itoh, T. Akutsu and M. Kanehisa,
Clustering of database sequences for fast homology search
using upper bounds on alignment score,
Genome Informatics, 151
(The 4th Int. Workshop on Bioinformatics and Systems Biology),
93104, 2004.

T. Akutsu, M. Hayashida, E. Tomita, J. Suzuki and K. Horimoto,
Protein threading with profiles and constraints,
Proc. IEEE 4th Symp. Bioinformatics and Bioengineering (BIBE 2004),
537544, 2004.

Dukka Bahadur K.C., T. Akutsu, E. Tomita and T. Seki,
Protein sidechain packing problem: a maximum edgeweight
clique algorithmic approach,
Proc. 2nd AsiaPacific Bioinformatics Conference (APBC 2004),
191200, 2004.

K. F. Aoki, A. Yamaguchi, Y. Okuno, T. Akutsu, N. Ueda, M. Kanehisa and
H. Mamitsuka,
Efficient treematching methods for accurate carbohydrate database queries,
Genome Informatics 2003, 134143, 2003.

D. Fukagawa and T. Akutsu,
Performance analysis of a greedy algorithm for inferring boolean functions,
Proc. 6th Int. Conf. Discovery Science (DS 2003),
Lecture Notes in Artificial Intelligence 2843, 114127, 2003.

T. Akutsu,
Efficient extraction of mapping rules of atoms from enzymatic reaction data,
Proc. 7th Int. Conf. Computational Molecular Biology (RECOMB 2003),
18, 2003.

K. C. D. Bahadur, T. Akutsu, E. Tomita, T. Seki and A. Fujiyama,
Point matching under nonuniform distortions and protein side chain packing
based on an efficient maximum clique algorithm,
Genome Informatics, 13, 143152, 2002.

T. Akutsu and S. Ott,
Inferring a union of halfspaces from examples,
Proc. 8th International Conference on Computing and Combinatorics (COCOON 2002),
Lecture Notes in Computer Science 2387, 117126, 2002.

T. Akutsu, H. Bannai, S. Miyano and S. Ott,
On the complexity of deriving position specific score matrices from
examples,
Proc. 13th Annual Symposium on Combinatorial Pattern Matching (CPM 2002),
Lecture Notes in Computer Science 2373, 168177, 2002.

T. Akutsu and K. Horimoto,
Local multiple alignment of numerical sequences:
detection of subtle motifs from protein sequences and structures,
Genome Informatics, 12, 8392, 2001.

T. Akutsu,
A local search algorithm for local multiple alignment:
special case analysis and application to cancer classification,
Proc. 2001 International Conference on Parallel
and Distributed Processing Techniques and Applications (PDPTA 2001),
12841290, 2001.

T. Akutsu and S. Miyano,
Selecting informative genes for cancer classification
using gene expression data,
2001 IEEEEURASIP Workshop on
Nonlinear Signal and Image Processing (NSIP),
in CDROM BOOK, 2001.

T. Akutsu, S. Miyano and S. Kuhara,
A simple greedy algorithm for finding functional relations:
efficient implementation and average case analysis,
Proc. The Third International Conference on Discovery Science (DS 2000),
Lecture Notes in Artificial Intelligence 1967, 8698, 2000.

T. Akutsu, H. Arimura and S. Shimozono,
On approximation algorithms for local multiple alignment,
Proc. 4th Int. Conf. Computational Molecular Biology (RECOMB 2000),
17, 2000.

T Akutsu, S. Miyano and S. Kuhara,
Algorithms for identifying Boolean networks and related biological
networks based on matrix multiplication and fingerprint function,
Proc. 4th Int. Conf. Computational Molecular Biology (RECOMB 2000),
814, 2000.

T Akutsu, S. Miyano and S. Kuhara,
Algorithms for inferring qualitative models of biological networks,
Proc. Pacific Symposium on Biocomputing 2000 (PSB 2000), 290301, 2000.

T.Akutsu and K.L.Sim,
Protein threading based on multiple protein structure alignment,
Genome Informatics 1999 (GIW '99), 2329, 1999.

T. Akutsu, K. Kanaya, A. Ohyama and A. Fujiyama,
Matching of spots in 2D electrophoresis images.
Point matching under nonuniform distortions,
Proc. 10th Annual Symposium on Combinatorial Pattern Matching
(CPM '99), Lecture Notes in Computer Science 1645, 212222, 1999.

T. Akutsu, S. Miyano and S. Kuhara,
Identification of genetic networks from a small number of
gene expression patterns under the boolean network model,
Proc. Pacific Symposium on Biocomputing '99 (PSB '99),
1728, 1999.

T. Akutsu, S. Kuhara, O. Maruyama and S. Miyano,
A system for identifying genetic networks from gene expression patterns
produced by gene disruptions and overexpressions,
Genome Informatics 1998 (GIW '98), 151160, 1998.

T. Akutsu,
Approximation and exact algorithms for RNA secondary structure
prediction and recognition of stochastic contextfree languages,
Proc. 9th Annual International Symposium on
Algorithms and Computation (ISAAC '98),
Lecture Notes in Computer Science 1533, 337346, 1998.

T. Akutsu and M. Yagiura,
On the complexity of deriving score functions from examples
for problems in molecular biology,
Proc. 25th Int. Colloquium on Automata, Languages, and Programming (ICALP '98),
Lecture Notes in Computer Science 1443, 832843, 1998.

T. Akutsu, S. Kuhara, O. Maruyama and S. Miyano,
Identification of gene regulatory networks by strategic gene disruptions
and gene overexpressions,
Proc. 9th Annual ACMSIAM Symposium on Discrete Algorithms (SODA '98),
695702, 1998.

T. Akutsu and H. Tashimo,
Linear programming based approach to the derivation of a contact
potential for protein threading,
Proc. Pacific Symposium on Biocomputing '98 (PSB '98),
413424, 1998.

T. Akutsu and S. Miyano,
On the approximation of protein threading,
Proc. First Annual International Conference on Computational Molecular Biology
(RECOMB '97), 38, 1997.

T. Akutsu, H. Tamaki and T. Tokuyama,
Distribution of distances and triangles in a point set and algorithms
for computing the largest common point set,
Proc. the 13th ACM Symposium on Computational Geometry, 314323, 1997.

T. Akutsu and F. Bao,
Approximating minimum keys and optimal substructure screens,
Proc. 2nd International Conference on Computing and Combinatorics (COCOON '96)
(LNCS 1090), 290299, 1996.

T. Akutsu and H. Tashimo,
Protein structure comparison using representation by line segment sequences,
Proc. Pacific Symposium on Biocomputing '96 (PSB '96),
2540, 1996.

T. Akutsu, K. Onizuka and M. Ishikawa,
New hashing techniques and their application to a protein
structure database system,
Proc. 28th Hawaii Int. Conf. System Sciences (HICSS28)
5, 197206, 1995.

T. Akutsu,
On determining the
congruity of point sets in higher dimensions,
Proc. 5th International Symposium on Algorithms and Computation (ISAAC '94)
(LNCS 834), 3846, 1994.

T. Akutsu and M. M. Halldorson,
On the approximation of largest common subtrees and largest common point sets,
Proc. 5th Annual International Symposium on
Algorithms and Computation (ISAAC '94)(LNCS 834), 405413, 1994.

T. Akutsu,
Approximate string matching with don't care characters,
Proc. 5th International Symposium on Combinatorial Pattern Matching
(CPM '94)(LNCS 807), 240249, 1994.

T. Akutsu,
Efficient and robust threedimensional pattern matching algorithms using
hashing and dynamic programming techniques,
Proc. 27th Hawaii Int. Conf. System Sciences (HICSS27), 225234, 1994.

T. Akutsu,
A linear time pattern matching algorithm between a string and a tree,
Proc. 4th International Symposium on Combinatorial Pattern Matching
(CPM '93)(LNCS 684), 110, 1993.

T. Akutsu and A. Takasu,
Inferring approximate functional dependencies from example data,
Proc. AAAI93 Workshop on Knowledge Discovery in Databases,
138152, 1993.

T. Akutsu and A. Takasu,
On PAC learnability of functional dependencies,
Proc. Workshop on Algorithmic Learning Theory (ALT '92), 229239, 1992.

T. Akutsu,
Algorithms for determining the geometrical congruity in two and three
dimensions,
Proc. 3rd International Symposium on
Algorithms and Computation (ISAAC '92)(LNCS 834), 279288, 1992.

T. Akutsu,
On the number of hands required to disassemble a composite object,
Proc. 2nd International Symposium on Measurement and Control in
Robotics (ISMCR '92), 6368, 1992.

T. Akutsu, S. Yaoi, K. Sato and S. Enomoto,
Development and comparison of search algorithms for robot motion
planning in the configuration space,
IEEE/RSJ International Workshop on Intelligent Robotics and Systems (IROS '91),
429434, 1991.

T. Akutsu, Y. Aoki, S. Hasegawa, H. Imai and T. Tokuyama,
The sum of smaller endpoint degree over edges of graphs and its applications
to geometric problems,
Proc. 3rd Canadian Conference on Computational Geometry, 145148, 1991.

T. Akutsu and S. Ohsuga,
CHEMILOG  a logic programming language/system for chemical information
processing,
Proc. International Conference on Fifth Generation Computer Systems 1998
(FGCS '88),
11761183, 1988.
Book Chapters

F. Wang, T. Akutsu, and T. Mori.
Metrics for RNA secondary structure comparison,
Methods in Molecular Biology, 2586, 7988, 2023.

Z. Chen, X. Liu, F. Li, C. Li, T. MarquezLago, A. Leier, G. I. Webb, D. Xu, T. Akutsu, and J. Song,
Systematic characterization of lysine posttranslational modification sites
ising MUscADEL,
Methods in Molecular Biology, 2499, 205219, 2022.

N. Nakajima, T. Akutsu, and R. Nakato,
Databases for proteinprotein interactions,
Methods in Molecular Biology, 2361, 229248, 2021.

T. Akutsu,
Analysis of Boolean networks and Boolean models of metabolic networks,
Application of Omics, AI and Blockchain in Bioinformatics Research
(J. JP. Tsai and KL. Ng, eds.),
World Scientific, 2019.

J. C. Nacher and T. Akutsu,
Controllability methods for identifying associations between critical control ncRNAs and human diseases,
Methods in Molecular Biology, 1912, 289300, 2019.

T. Tamura and T. Akutsu,
Theory and method of completion for a Boolean regulatory network
using observed data,
Biological Data Mining and Its Applications in Healthcare,
Science, Engineering, and Biology Informatics: Volume 8
(XL Li, SK Ng and J. TL. Wang, eds.), World Scientific,
123146, 2014.

E. Tomita, T. Akutsu and T. Matsunaga,
Efficient algorithms for finding maximum and maximal cliques:
Effective tools for bioinformatics,
Biomedical Engineering, Trends in Electronics, Communications and
Software (A. N. Laskovski, ed.), InTech, 625640, 2011.

T. Akutsu,
Sequence alignment algorithms: Applications to glycans and trees and treelike structures,
Handbook of Chemoinformatics Algorithms (JL Faulon and A. Bender, eds.),
CRC Press, 363381, 2010.

T. Akutsu and WK. Ching,
Analysis and control of deterministic and probabilistic Boolean networks,
Elements of Computational Systems (H. M. Lodhi and S. H. Muggleton, eds.),
Wiley, 235255, 2010.

T. Akutsu and M. Hayashida,
Domainbased prediction and analysis of proteinprotein interactions,
Biological Data Mining in Protein Interaction Networks
(XL Li and SK Ng, eds.), IGI Global, 2944, 2009.

T. Akutsu,
Algorithmic aspects of protein threading,
Advanced Data Mining Technologies in Bioinformatics (HH Hsu, ed.),
Idea Group Pub., 118135, 2006.

JP. Vert, H. Saigo and T. Akutsu,
Local alignment kernels for biological sequences,
Kernel Methods in Computational Biology (B. Schoelkopf, K. Tsuda and JP. Vert, eds.)
The MIT Press, 131153, 2004.

T. Akutsu and S. Miyano,
Selecting informative genes for cancer classification using gene expression data,
Computational and Statistical Approaches to Genomics
(W. Zhang and I. Shmulevich, eds.), Kluwer Academic Pub., 7991, 2002.
UP