Systems Biology Colloquium

This is a series of invited colloquiual lectures provided by top researchers in the field of systems biology, theoretical and computational biology, bioinformatics and related fields of applied mathematics and computer science. The series has been founded in collaboration with Global Change Research Centre AS CR as a part of the ESF co-funded project CyanoTeam.

Lectures run irregularly during the academic year with respect to the time schedule provided on this web page.

Invited Talk

TITLE: Boolean Network Identification from Multiplex Time Series Data

Loic Pauleve

  • When: 27th of November 2015, 10am
  • Where: Faculty of Informatics MU, Botanická 68a, room A418
  • Who: Loïc Paulevé (LRI, Université Paris-Sud)

[ Research Profile ]


Boolean networks (and more general logic models) are useful frameworks to study signal transduction across multiple pathways. Logical models can be learned from a prior knowledge network structure and multiplex phosphoproteomics data. However, most efficient and scalable training methods focus on the comparison of two time-points and assume that the system has reached an early steady state. In this paper, we generalize such a learning procedure to take into account the time series traces of phosphoproteomics data in order to discriminate Boolean networks according to their transient dynamics. To that goal, we exhibit a necessary condition that must be satisfied by a Boolean network dynamics to be consistent with a discretized time series trace. Based on this condition, we use a declarative programming approach (Answer Set Programming) to compute an over-approximation of the set of Boolean networks which fit best with experimental data. Combined with modelchecking approaches, we end up with a global learning algorithm and compare it to learning approaches based on static data.

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