Algorithmic and complexity results for decompositions of biological networks into monotone subsystems

Bhaskar DasGupta, German A. Enciso, Eduardo Sontag, Yi Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

A useful approach to the mathematical analysis of large-scale biological networks is based upon their decompositions into monotone dynamical systems. This paper deals with two computational problems associated to finding decompositions which are optimal in an appropriate sense. In graph-theoretic language, the problems can be recast in terms of maximal sign-consistent subgraphs. The theoretical results include polynomial-time approximation algorithms as well as constant-ratio inapproximability results. One of the algorithms, which has a worst-case guarantee of 87.9% from optimality, is based on the semidefinite programming relaxation approach of Goemans-Williamson [14]. The algorithm was implemented and tested on a Drosophila segmentation network [7] and an Epidermal Growth Factor Receptor pathway model [25], and it was found to perform close to optimally.

Original languageEnglish (US)
Title of host publicationExperimental Algorithms - 5th International Workshop, WEA 2006, Proceedings
PublisherSpringer Verlag
Pages253-264
Number of pages12
ISBN (Print)3540345973, 9783540345978
StatePublished - 2006
Event5th International Workshop on Experimental Algorithms, WEA 2006 - Cala Galdana, Menorca, Spain
Duration: May 24 2006May 27 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4007 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Workshop on Experimental Algorithms, WEA 2006
Country/TerritorySpain
CityCala Galdana, Menorca
Period5/24/065/27/06

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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