A novel method for signal transduction network inference from indirect experimental Evidence

Reka Z. Albert, Bhaskar DasGupta, Riccardo Dondi, Sema Kachalo, Eduardo Sontag, Alexander Zelikovsky, Kelly Westbrooks

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

Abstract

In this paper we introduce a new method of combined synthesis and inference of biological signal transduction networks. A main idea of our method lies in representing observed causal relationships as network paths and using techniques from combinatorial optimization to find the sparsest graph consistent with all experimental observations. Our contributions are twofold: on the theoretical and algorithmic side, we formalize our approach, study its computational complexity and prove new results for exact and approximate solutions of the computationally hard transitive reduction substep of the approach. On the application side, we validate the biological usability of our approach by successfully applying it to a previously published signal transduction network by Li et al. [20] and show that our algorithm for the transitive reduction substep performs well on graphs with a structure similar to those observed in transcriptional regulatory and signal transduction networks.

Original languageEnglish (US)
Title of host publicationAlgorithms in Bioinformatics - 7th International Workshop, WABI 2007, Proceedings
Pages407-419
Number of pages13
StatePublished - Dec 24 2007
Event7th International Workshop on Algorithms in Bioinformatics, WABI 2007 - PhiIadelphia, PA, United States
Duration: Sep 8 2007Sep 9 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4645 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Workshop on Algorithms in Bioinformatics, WABI 2007
CountryUnited States
CityPhiIadelphia, PA
Period9/8/079/9/07

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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