Date |
2:00pm Apr 12, 2022 |
Speaker |
Edda Klipp
Humboldt University of Berlin
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Title |
Mathematical modeling of signaling networks in time and space
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Abstract
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Signaling pathways relay information about changes inside and outside
of the cell to specific recipients such as transcription factors or
metabolic enzymes. The experimental investigation of signaling
pathways has created an enormous amount of facts and data of different
type. In order to integrate such data and to allow derivation of
concepts, mathematical modeling is instrumental.
Here, we present an overview of computational modeling techniques
ranging from Boolean modeling to differential equations, from dynamics
without considering space to spatio-temporal processes as well as
including stochastic and deterministic approaches. We discuss the
applicability of the approaches given the available amount and
character of data and we show some examples where mathematical
modeling was crucial to understand the logic, dynamics and regulation
of cellular signaling processes. We also discuss the amount of
information that a pathway can transmit depending on its wiring and
parameters.
Based on a recent data set, we discuss first steps and future concepts
for the integration of time-resolved mRNA, proteome and
phospho-proteome data into dynamic signaling networks.
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