NET-SYNTHESIS: A software for synthesis, inference and simplification of signal transduction networks

Sema Kachalo; Ranran Zhang; Eduardo Sontag; Réka Albert; Bhaskar DasGupta

doi:10.1093/bioinformatics/btm571

NET-SYNTHESIS: A software for synthesis, inference and simplification of signal transduction networks

Sema Kachalo, Ranran Zhang, Eduardo Sontag, Réka Albert, Bhaskar DasGupta

Research output: Contribution to journal › Article › peer-review

33 Scopus citations

Abstract

We present a software for combined synthesis, inference and simplification of signal transduction networks. The main idea of our method lies in representing observed indirect causal relationships as network paths and using techniques from combinatorial optimization to find the sparsest graph consistent with all experimental observations. We illustrate the biological usability of our software by applying it to a previously published signal transduction network and by using it to synthesize and simplify a novel network corresponding to activation-induced cell death in large granular lymphocyte leukemia.

Original language	English (US)
Pages (from-to)	293-295
Number of pages	3
Journal	Bioinformatics
Volume	24
Issue number	2
DOIs	https://doi.org/10.1093/bioinformatics/btm571
State	Published - Jan 15 2008

All Science Journal Classification (ASJC) codes

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/btm571

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title = "NET-SYNTHESIS: A software for synthesis, inference and simplification of signal transduction networks",

abstract = "We present a software for combined synthesis, inference and simplification of signal transduction networks. The main idea of our method lies in representing observed indirect causal relationships as network paths and using techniques from combinatorial optimization to find the sparsest graph consistent with all experimental observations. We illustrate the biological usability of our software by applying it to a previously published signal transduction network and by using it to synthesize and simplify a novel network corresponding to activation-induced cell death in large granular lymphocyte leukemia.",

author = "Sema Kachalo and Ranran Zhang and Eduardo Sontag and R{\'e}ka Albert and Bhaskar DasGupta",

note = "Funding Information: This project was partially supported by NSF grants IIS-0346973 (to S.K.), EIA-0205116 and DMS-050455 (to E.D.S.), MCB-0618402 and CCF-0643529 (to R.A.), IIS-0346973, IIS-0612044 and DBI-0543365 (to B.D.) and USDA grant 2006-35100-17254 (to R.A.).",

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doi = "10.1093/bioinformatics/btm571",

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T2 - A software for synthesis, inference and simplification of signal transduction networks

AU - Kachalo, Sema

AU - Zhang, Ranran

AU - Sontag, Eduardo

AU - Albert, Réka

AU - DasGupta, Bhaskar

N1 - Funding Information: This project was partially supported by NSF grants IIS-0346973 (to S.K.), EIA-0205116 and DMS-050455 (to E.D.S.), MCB-0618402 and CCF-0643529 (to R.A.), IIS-0346973, IIS-0612044 and DBI-0543365 (to B.D.) and USDA grant 2006-35100-17254 (to R.A.).

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N2 - We present a software for combined synthesis, inference and simplification of signal transduction networks. The main idea of our method lies in representing observed indirect causal relationships as network paths and using techniques from combinatorial optimization to find the sparsest graph consistent with all experimental observations. We illustrate the biological usability of our software by applying it to a previously published signal transduction network and by using it to synthesize and simplify a novel network corresponding to activation-induced cell death in large granular lymphocyte leukemia.

AB - We present a software for combined synthesis, inference and simplification of signal transduction networks. The main idea of our method lies in representing observed indirect causal relationships as network paths and using techniques from combinatorial optimization to find the sparsest graph consistent with all experimental observations. We illustrate the biological usability of our software by applying it to a previously published signal transduction network and by using it to synthesize and simplify a novel network corresponding to activation-induced cell death in large granular lymphocyte leukemia.

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NET-SYNTHESIS: A software for synthesis, inference and simplification of signal transduction networks

Abstract

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