Synthesis, Simplification and Analysis of Biological Networks Using Higher Order Topological Connect
summary
Describes three concrete methods and results: using modular response analysis reduced to a set multicover reduction to choose minimal perturbation experiments via a randomized algorithm; decomposing networks into monotone parts by maximizing sign-consistent edges with semi-definite programming and rounding — e.g. Drosophila single-cell network (13 nodes, 20 edges) yields 17 consistent edges (provably optimal) and an EGF model (852 edges) yields 633 consistent edges (provable bound ~728); a fast synthesis tool reproduces manual curation in seconds and an information‑theoretic degeneracy measure uses binary transitive reduction.
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chapters (8)
- 0:00Synthesis, Simplification and Analysis of Biological Networks Using Higher Order Topological Connectivities
- 1:08Modeling problem
- 3:42Reverse engineering
- 5:12Settings for modular response analysis method
- 12:21Monotonicity is closely related to positive and negative feedback loops The topic of analyzing the behaviors of such feedback loops is a long standing one in biology in the context of regulation, metabolism, and developments
- 12:56More advantages of studying monotone systems in many situations allow one to characterize the behavior of an entire system, based upon the qualitative knowledge represented by general network topology and the inhibitory or activating character of interconnections, combined with only a relathely
- 24:28Main computational step for network synthesis
- 25:22Plant signal transduction network consistent guard cell signal transduction network for ABA- induced stomatal closure
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