References, resources and related tools
References
- Agrawal, R., Imielinski, T. & Swami, A. "Mining Association Rules between Sets of Items in Large Databases" in ACM SIGMOD Conference (eds. Buneman, P. & Jajodia, S.) 207-216 (ACM Press, 1993).
- Aitchison, J., "A Concise Guide to Compositional Data Analysis" in CDA Workshop Girona (2003).
- Brown, M.B., "A Method for Combining Non-Independent, One-Sided Tests of Significance." Biometrics 31, 987-992 (1975).
- Costello, E.K. et al. "Bacterial Community Variation in Human Body Habitats Across Space and Time." Science 326, 1694-1697 (2009).
- Ellson, J., Gansner, E.R., Koutsofios, E., North, S.C. & Woodhull, G. in GRAPH DRAWING SOFTWARE (Springer-Verlag, 2003).
- Faith J.J., et al. "Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles." PLoS Biol, 5:54-66 (2007).
- Hu, Z. et al. "VisANT 3.5: multi-scale network visualization, analysis and inference based on the gene ontology." Nucleic Acids Research 37, W115-W121 (2009).
- Lallich S., Teytaud O., & Prudhomme E. "Statistical inference and data mining: false discoveries control." 17th Compstat Symposium of the IASC:325-336 (2006).
- Legendre, P. & Legendre, L. "Numerical ecology" (Elsevier Science B.V., Amsterdam, 1983).
- Margolin, A.A. et al. "ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context." BMC Bioinformatics, 1-15 (2006)
- Meyer, P.E., Lafitte, F. & Bontempi, G. "minet: A R/Bioconductor Package for Inferring Large Transcriptional Networks Using Mutual Information." BMC Bioinformatics, 1-10 (2009)
- Meyer P.E., et al. "Information-theoretic inference of large transcriptional regulatory networks." EUROSIP J. Bioinform. Syst. Biol. 79879 (2007).
Resources
Below, resources are listed of which CoNet makes use.
Links to some related tools
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ARACNE (standalone)
http://wiki.c2b2.columbia.edu/califanolab/index.php/Software/ARACNE
gene regulatory network inference algorithm, Califano lab
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BANJO (standalone and Java library)
http://www.cs.duke.edu/~amink/software/banjo/
Banjo is a software application and framework for structure learning of static and dynamic Bayesian networks,
Alexander J. Hartemink and colleagues
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BNW
http://compbio.uthsc.edu/BNW/sourcecodes/home.php
Bayesian Network Webserver for Biological Network Modeling, by Jesse D. Ziebarth, Anindya Bhattacharya and Yan Cui
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compare-profiles (RSAT tool suite, command line tool)
http://rsat.ulb.ac.be/rsat
compare all pairs of rows in a matrix using one of several measures, by Jacques van Helden
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Community Analyzer (stand alone)
http://metagenomics.atc.tcs.com/Community_Analyzer/
explores inter-microbial interactions across metagenomes, TATA Consultancy Services, Bio-Sciences Division
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ccrepe
http://huttenhower.sph.harvard.edu/ccrepe
R package designed to detect significant correlations in compositional data, Huttenhower lab
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Cyni Toolbox (Cytoscape plugin)
http://apps.cytoscape.org/apps/cynitoolbox
Cytoscape Network Inference Toolbox puts together several tools that allow inferring networks from bio data, Benno Schwikowski and Oriol Guitart Pla
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efficient estimation of covariance and (partial) correlation
http://strimmerlab.org/software/corpcor/
R package with shrinkage estimator for covariance matrix, Strimmer lab
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ExpressionCorrelation (Cytoscape plugin)
http://www.baderlab.org/Software/ExpressionCorrelation
computes a similarity network from either the genes or conditions in an expression matrix, Bader lab
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Fast Local Similarity Analysis (stand alone)
http://hallam.microbiology.ubc.ca/fastLSA/install/index.html
computes a directed similarity network from time series data, Hallam lab
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Extended Local Similarity Analysis (LSA) (standalone and as part of the Galaxy pipeline)
http://meta.usc.edu/softs/lsa/
computes a directed similarity network from time series data, Sun lab
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GeneNet (R package)
http://strimmerlab.org/software/genenet/index.html
GeneNet is an R package for learning high-dimensional dependency networks from genomic data
(e.g. gene association networks), Strimmer lab
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MENA (web server)
http://ieg2.ou.edu/MENA
Molecular Ecological Network Analysis Pipeline, Zhou lab
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MONET (Cytoscape plugin and web service)
http://monet.kisti.re.kr
regulatory network inference algorithm based on Bayesian network learning, by Phil Hyoun Lee and Doheon Lee
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NetCutter (stand alone)
http://muller.group.ifom-ieo-campus.it/
co-occurrence networks identification and analysis, by Heiko Mueller and Francesco Mancuso
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Picante (R package)
http://picante.r-forge.r-project.org/
phylogeny and trait diversity, community null models, by Peter Cowan, Matthew Helmus and Steven Kembel
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SparCC (stand alone)
https://bitbucket.org/yonatanf/sparcc
Python module for computing correlations in compositional data, by Yonatan Friedman
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WGCNA
http://labs.genetics.ucla.edu/horvath/CoexpressionNetwork/Rpackages/WGCNA/
R package for weighted correlation network analysis, by Peter Langfelder and Steve Horvath