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Identifying gene regulatory networks from experimental data

Authors:

Ting Chen,

Vladimir Filkov,

Steven S. SkienaAuthors Info & Claims

RECOMB '99: Proceedings of the third annual international conference on Computational molecular biology

Pages 94 - 103

https://doi.org/10.1145/299432.299462

Published: 01 April 1999 Publication History

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Emadi MBoroujeni FPirgazi J(2024)Gene regulatory network inference from gene expression data based on knowledge matrix and improved rotation forestBiomedical Signal Processing and Control10.1016/j.bspc.2024.10599292(105992)Online publication date: Jun-2024
https://doi.org/10.1016/j.bspc.2024.105992
Gao NMinhaz Ud-Dean SGunawan R(2016)Gene Regulatory Network Inference Using Time-Stamped Cross-Sectional Single Cell Expression DataIFAC-PapersOnLine10.1016/j.ifacol.2016.12.11749:26(147-152)Online publication date: 2016
https://doi.org/10.1016/j.ifacol.2016.12.117
Aditya SDasGupta BKarpinski M(2013)Algorithmic Perspectives of Network Transitive Reduction Problems and their Applications to Synthesis and Analysis of Biological NetworksBiology10.3390/biology30100013:1(1-21)Online publication date: 19-Dec-2013
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Published In

RECOMB '99: Proceedings of the third annual international conference on Computational molecular biology

April 1999

332 pages

ISBN:1581130694

DOI:10.1145/299432

Chairmen:
Sorin Istrail
Sandia National Labs
,
Pavel Pevzner
Univ. of Southern California, Los Angeles
,
Michael Waterman
Univ. of Southern California, Los Angeles

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 April 1999

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INRIA

RECOMB99: 3rd International Conference on Computational Molecular Biology

April 11 - 14, 1999

Lyon, France

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Overall Acceptance Rate 148 of 538 submissions, 28%

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Emadi MBoroujeni FPirgazi J(2024)Gene regulatory network inference from gene expression data based on knowledge matrix and improved rotation forestBiomedical Signal Processing and Control10.1016/j.bspc.2024.10599292(105992)Online publication date: Jun-2024
https://doi.org/10.1016/j.bspc.2024.105992
Gao NMinhaz Ud-Dean SGunawan R(2016)Gene Regulatory Network Inference Using Time-Stamped Cross-Sectional Single Cell Expression DataIFAC-PapersOnLine10.1016/j.ifacol.2016.12.11749:26(147-152)Online publication date: 2016
https://doi.org/10.1016/j.ifacol.2016.12.117
Aditya SDasGupta BKarpinski M(2013)Algorithmic Perspectives of Network Transitive Reduction Problems and their Applications to Synthesis and Analysis of Biological NetworksBiology10.3390/biology30100013:1(1-21)Online publication date: 19-Dec-2013
https://doi.org/10.3390/biology3010001
Chavez-Alvarez RChavoya ALopez-Martin C(2012)Finding the minimal gene regulatory function in the presence of undefined transitional states using a genetic algorithmProceedings of the 9th international conference on Information Processing in Cells and Tissues10.1007/978-3-642-28792-3_29(238-249)Online publication date: 31-Mar-2012
https://dl.acm.org/doi/10.1007/978-3-642-28792-3_29
Čepek OKronus DKučera P(2010)Analysing DNA microarray data using Boolean techniquesAnnals of Operations Research10.1007/s10479-010-0723-0188:1(77-110)Online publication date: 24-Feb-2010
https://doi.org/10.1007/s10479-010-0723-0
Albert RDasGupta BSontag E(2010)Inference of Signal Transduction Networks from Double Causal EvidenceComputational Biology10.1007/978-1-60761-842-3_16(239-251)Online publication date: 17-Aug-2010
https://doi.org/10.1007/978-1-60761-842-3_16
Yoo C(2010)Discovering Gene–Gene and Gene–Environment Causal Interactions Using Bioinformatics ApproachesEnvironmental Factors, Genes, and the Development of Human Cancers10.1007/978-1-4419-6752-7_5(115-138)Online publication date: 18-Aug-2010
https://doi.org/10.1007/978-1-4419-6752-7_5
Liu WWang BGlassey JMartin EZhao J(2009)A novel methodology for finding the regulation on gene expression dataProgress in Natural Science10.1016/j.pnsc.2008.07.00319:2(267-272)Online publication date: Feb-2009
https://doi.org/10.1016/j.pnsc.2008.07.003
Zoppis IMauri G(2008)Clustering Dependencies with Support VectorsTrends in Intelligent Systems and Computer Engineering10.1007/978-0-387-74935-8_11(155-165)Online publication date: 2008
https://doi.org/10.1007/978-0-387-74935-8_11
Yu ZWang LHildebrandt MSchaid D(2008)Testing whether genetic variation explains correlation of quantitative measures of gene expression, and application to genetic network analysisStatistics in Medicine10.1002/sim.327427:19(3847-3867)Online publication date: 28-Apr-2008
https://doi.org/10.1002/sim.3274
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Soft computing methods to predict gene regulatory networks: An integrative approach on time-series gene expression data

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