Modeling evolution of crosstalk in noisy signal transduction networks.

Signal transduction networks can form highly interconnected systems within cells due to crosstalk between constituent pathways. To better understand the evolutionary design principles underlying such networks, we study the evolution of crosstalk for two parallel signaling pathways that arise via gene duplication. We use a sequence-based evolutionary algorithm and evolve the network based on two physically motivated fitness functions related to information transmission. We find that one fitness function leads to a high degree of crosstalk while the other leads to pathway specificity. Our results offer insights on the relationship between network architecture and information transmission for noisy biomolecular networks.

• Publication year

  2017

• Venue

  Physical Review E

• Publication date

  2017-07-05

• Fields of study

  Biology, Medicine, Physics, Computer Science

• Identifiers
  DOI 10.1103/PhysRevE.97.020402arXiv 1707.01467PMID 29548149PMCID PMC5973540
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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