Talk:Biological network inference

Untitled
I'd love to see this expanded upon. As a neurobiologist with no real programming experience, I've been struggling with how to turn tons of microarray expression data I have acquired into bonafide depictions of gene regulatory networks. I've tried several of the off-the-shelf programs with little luck. Reading the primary literature isn't getting me anywhere. 68.46.183.96 (talk) 20:22, 11 July 2008 (UTC)

move refs here
This is just a dump of articles with unclear relation to what's written in the article. Moving them here. Headbomb {{{sup|ταλκ}}κοντριβς – WP Physics} 20:21, 25 August 2009 (UTC)


 * Margolin, A.A., et al., Reverse engineering cellular networks. Nature Protocols, 2006. 1(2): p. 663-672. (full description of ARACNE algorithm)
 * Margolin, A.A., et al., ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics, 2006. 7(Suppl1): p. S1-7.
 * Markowetz, F. A bibliography on learning causal networks of gene interactions (July 31, 2006).[available from: http://www.molgen.mpg.de/~markowet/doc/network-bib.pdf; http://genomics.princeton.edu/~florian/docs/network-bib.pdf]
 * Meyer P.E., Kontos K., Lafitte F., Bontempi G. Information-Theoretic Inference of Large Transcriptional Regulatory Networks [available from: http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2007/79879]
 * Papin, J.A., et al., Reconstruction of cellular signalling networks and analysis of their properties. Nat. Rev. Mol. Cell Biol., 2005. 6(2): p. 99-111.
 * Pe'er, D., et al., Inferring subnetworks from perturbed expression profiles. Bioinformatics, 2001. 17: p. 215S-224S.
 * Pe'er, D. Bayesian Network Analysis of Signaling Networks: A Primer. Science STKE 2005 [on-line primer]. Available from: www.stke.org/content/full/sigtrans.
 * Perrin, B.E., et al., Gene networks inference using dynamic Bayesian networks. Bioinformatics, 2003. 19(S2): p. ii138-ii148.
 * Sachs, K., et al., Causal protein-signaling networks derived from multiparameter single-cell data. Science, 2005. 308: p. 523-529.
 * Schadt, E.E., et al., An integrative genomics approach to infer causal associations between gene expressiona and disease. Nat. Genet., 2005. 37(7): p. 710-717.
 * Segal, E., R. Yelensky, and D. Koller, Genome-wide discovery of transcriptional modules from DNA sequence and gene expression. Bioinformatics, 2003. 19(Suppl1): p. i264-272.
 * Segal, E., et al., Rich probabilistic models for gene expression. Bioinformatics, 2001. 17(Suppl1): p. S243-252.
 * Shannon, P., et al., Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res., 2003. 13(11): p. 2498-504.
 * Singhal, M. and K. Domico, CABIN: Collective Analysis of Biological Interaction Networks. Journal of Computational Biology and Chemistry, (accepted for publication in 2007)
 * Taylor, R.C., et al., SEBINI: Software Environment for BIological Network Inference. Bioinformatics, 2006. 21: p. 2706-2708.
 * Troyanskaya, O.G., et al., A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae). Proc. Natl. Acad. Sci. USA, 2003. 100: p. 8348-8353.
 * van Someren, E.P., et al., Genetic network modeling. Pharmacogenomics, 2002. 3(4): p. 507-25.
 * Weaver, D.C., C.T. Workman, and G.D. Stromo, Modeling regulatory networks with weight matrices. Pac. Symp. Biocomput., 1999.
 * Werhli, A.V., M. Grezegorczyk, and D. Husmeier, Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks. Bioinformatics, 2006. 22(20): p. 2523-2531.
 * Wessels, L.F., E.P. van Someren, and M.J. Reinders, A comparison of genetic network models. Pac. Symp. Biocomput., 2001.
 * Yu, H., et al., Advances to bayesian network inference for generating causal networks form observational biological data. Bioinformatics, 2004. 20: p. 3594-3603.
 * Zhao, W., E. Serpedin, and E.R. Dougherty, Inferring gene regulatory networks from time series data using the minimum description length principle. Bioinformatics, 2006. 22(17): p. 2129-35.
 * Zhou, X., et al., A Bayesian connectivity-based approach to constructing probabilistic gene regulatory networks. Bioinformatics, 2004. 20(17): p. 2918-27.
 * Zou, M. and S.D. Conzen, A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course data. Bioinformatics, 2005. 21(1): p. 71-79.
 * Papin, J.A., et al., Reconstruction of cellular signalling networks and analysis of their properties. Nat. Rev. Mol. Cell Biol., 2005. 6(2): p. 99-111.
 * Pe'er, D., et al., Inferring subnetworks from perturbed expression profiles. Bioinformatics, 2001. 17: p. 215S-224S.
 * Pe'er, D. Bayesian Network Analysis of Signaling Networks: A Primer. Science STKE 2005 [on-line primer]. Available from: www.stke.org/content/full/sigtrans.
 * Perrin, B.E., et al., Gene networks inference using dynamic Bayesian networks. Bioinformatics, 2003. 19(S2): p. ii138-ii148.
 * Sachs, K., et al., Causal protein-signaling networks derived from multiparameter single-cell data. Science, 2005. 308: p. 523-529.
 * Schadt, E.E., et al., An integrative genomics approach to infer causal associations between gene expressiona and disease. Nat. Genet., 2005. 37(7): p. 710-717.
 * Segal, E., R. Yelensky, and D. Koller, Genome-wide discovery of transcriptional modules from DNA sequence and gene expression. Bioinformatics, 2003. 19(Suppl1): p. i264-272.
 * Segal, E., et al., Rich probabilistic models for gene expression. Bioinformatics, 2001. 17(Suppl1): p. S243-252.
 * Shannon, P., et al., Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res., 2003. 13(11): p. 2498-504.
 * Singhal, M. and K. Domico, CABIN: Collective Analysis of Biological Interaction Networks. Journal of Computational Biology and Chemistry, (accepted for publication in 2007)
 * Taylor, R.C., et al., SEBINI: Software Environment for BIological Network Inference. Bioinformatics, 2006. 21: p. 2706-2708.
 * Troyanskaya, O.G., et al., A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae). Proc. Natl. Acad. Sci. USA, 2003. 100: p. 8348-8353.
 * van Someren, E.P., et al., Genetic network modeling. Pharmacogenomics, 2002. 3(4): p. 507-25.
 * Weaver, D.C., C.T. Workman, and G.D. Stromo, Modeling regulatory networks with weight matrices. Pac. Symp. Biocomput., 1999.
 * Werhli, A.V., M. Grezegorczyk, and D. Husmeier, Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks. Bioinformatics, 2006. 22(20): p. 2523-2531.
 * Wessels, L.F., E.P. van Someren, and M.J. Reinders, A comparison of genetic network models. Pac. Symp. Biocomput., 2001.
 * Yu, H., et al., Advances to bayesian network inference for generating causal networks form observational biological data. Bioinformatics, 2004. 20: p. 3594-3603.
 * Zhao, W., E. Serpedin, and E.R. Dougherty, Inferring gene regulatory networks from time series data using the minimum description length principle. Bioinformatics, 2006. 22(17): p. 2129-35.
 * Zhou, X., et al., A Bayesian connectivity-based approach to constructing probabilistic gene regulatory networks. Bioinformatics, 2004. 20(17): p. 2918-27.
 * Zou, M. and S.D. Conzen, A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course data. Bioinformatics, 2005. 21(1): p. 71-79.

Co-relation-based inference algorithms
1) from classical statistics - STUB
 * baseline: Pearson correlation

2) from information theory - STUB
 * Concept of mutual information
 * ARACNE algorithm
 * CLR algorithm
 * MRNET algorithm

3) from graphical probabilistic models - STUB
 * Bayesian network structure learning
 * K2 alg - needs a node ordering
 * BANJO toolkit

DREAM project - stub

Platforms for network inference - STUB
 * geWorkbench, Columbia
 * SEBINI

Visualization of inferred network - STUB
 * Cytoscape tool

Expansion of inferred network using public databases - data integration - STUB
 * CABIN tool

Changes 5/5/2022
This expansion is for CS4364. Please refrain from any changes until 5/13/2022 for grading purposes, thank you. — Preceding unsigned comment added by ErgoFoxy (talk • contribs) 19:47, 5 May 2022 (UTC)