Genome Biology

official impact factor 6.89

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Discovery of biological networks from diverse functional genomic data

Chad L Myers, Drew Robson, Adam Wible, Matthew A Hibbs, Camelia Chiriac, Chandra L Theesfeld, Kara Dolinski and Olga G Troyanskaya*

Genome Biology 2005, 6:R114 doi:10.1186/gb-2005-6-13-r114

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BioMed Central: 22 citations

Research article   Open Access

Removing bias against membrane proteins in interaction networks

Glauber C Brito, David W Andrews BMC Systems Biology 2011, 5:169 (19 October 2011)

Methodology article   Open Access Highly Accessed

Integrative approaches to the prediction of protein functions based on the feature selection

Seokha Ko, Hyunju Lee BMC Bioinformatics 2009, 10:455 (31 December 2009)

Software   Open Access Highly Accessed

Graphle: Interactive exploration of large, dense graphs

Curtis Huttenhower, Sajid O Mehmood, Olga G Troyanskaya BMC Bioinformatics 2009, 10:417 (14 December 2009)

Research   Open Access Highly Accessed

Gene networks in Drosophila melanogaster: integrating experimental data to predict gene function

James C Costello, Mehmet M Dalkilic, Scott M Beason, Jeff R Gehlhausen, Rupali Patwardhan, Sumit Middha, Brian D Eads, Justen R Andrews Genome Biology 2009, 10:R97 (16 September 2009)

The first computational interaction network built from Drosophila melanogaster protein-protein and genetic interaction data allows the functional annotation of orphan genes and reveals clusters of functionally-related genes.

Research article   Open Access Highly Accessed

The Symbiosis Interactome: a computational approach reveals novel components, functional interactions and modules in Sinorhizobium meliloti

Ignacio Rodriguez-Llorente, Miguel A Caviedes, Mohammed Dary, Antonio J Palomares, Francisco M Cánovas, José M Peregrín-Alvarez BMC Systems Biology 2009, 3:63 (16 June 2009)

Proceedings   Open Access

Assessing reliability of protein-protein interactions by integrative analysis of data in model organisms

Xiaotong Lin, Mei Liu, Xue-wen Chen BMC Bioinformatics 2009, 10(Suppl 4):S5 (29 April 2009)

Database   Open Access Highly Accessed

Towards systems genetic analyses in barley: Integration of phenotypic, expression and genotype data into GeneNetwork

Arnis Druka, Ilze Druka, Arthur G Centeno, Hongqiang Li, Zhaohui Sun, William TB Thomas, Nicola Bonar, Brian J Steffenson, Steven E Ullrich, Andris Kleinhofs, Roger P Wise, Timothy J Close, Elena Potokina, Zewei Luo, Carola Wagner, Günther F Schweizer, David F Marshall, Michael J Kearsey, Robert W Williams, Robbie Waugh BMC Genetics 2008, 9:73 (18 November 2008)

Method   Open Access

Combining guilt-by-association and guilt-by-profiling to predict Saccharomyces cerevisiae gene function

Weidong Tian, Lan V Zhang, Murat Taşan, Francis D Gibbons, Oliver D King, Julie Park, Zeba Wunderlich, J Michael Cherry, Frederick P Roth Genome Biology 2008, 9(Suppl 1):S7 (27 June 2008)

Method   Open Access

Inferring mouse gene functions from genomic-scale data using a combined functional network/classification strategy

Wan Kim, Chase Krumpelman, Edward M Marcotte Genome Biology 2008, 9(Suppl 1):S5 (27 June 2008)

Method   Open Access

GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function

Sara Mostafavi, Debajyoti Ray, David Warde-Farley, Chris Grouios, Quaid Morris Genome Biology 2008, 9(Suppl 1):S4 (27 June 2008)

Research   Open Access

Predicting gene function in a hierarchical context with an ensemble of classifiers

Yuanfang Guan, Chad L Myers, David C Hess, Zafer Barutcuoglu, Amy A Caudy, Olga G Troyanskaya Genome Biology 2008, 9(Suppl 1):S3 (27 June 2008)

Research   Open Access Highly Accessed

A critical assessment of Mus musculus gene function prediction using integrated genomic evidence

Lourdes Peña-Castillo, Murat Tasan, Chad L Myers, Hyunju Lee, Trupti Joshi, Chao Zhang, Yuanfang Guan, Michele Leone, Andrea Pagnani, Wan Kim, Chase Krumpelman, Weidong Tian, Guillaume Obozinski, Yanjun Qi, Sara Mostafavi, Guan Lin, Gabriel F Berriz, Francis D Gibbons, Gert Lanckriet, Jian Qiu, Charles Grant, Zafer Barutcuoglu, David P Hill, David Warde-Farley, Chris Grouios, Debajyoti Ray, Judith A Blake, Minghua Deng, Michael I Jordan, William S Noble, Quaid Morris, Judith Klein-Seetharaman, Ziv Bar-Joseph, Ting Chen, Fengzhu Sun, Olga G Troyanskaya, Edward M Marcotte, Dong Xu, Timothy R Hughes, Frederick P Roth et al. Genome Biology 2008, 9(Suppl 1):S2 (27 June 2008)

Research article   Open Access

High-precision high-coverage functional inference from integrated data sources

Bolan Linghu, Evan S Snitkin, Dustin T Holloway, Adam M Gustafson, Yu Xia, Charles DeLisi BMC Bioinformatics 2008, 9:119 (25 February 2008)

Research article   Open Access

Rank-based edge reconstruction for scale-free genetic regulatory networks

Guanrao Chen, Peter Larsen, Eyad Almasri, Yang Dai BMC Bioinformatics 2008, 9:75 (31 January 2008)

Research article   Open Access

Annotating novel genes by integrating synthetic lethals and genomic information

Daniel Schöner, Markus Kalisch, Christian Leisner, Lukas Meier, Marc Sohrmann, Mahamadou Faty, Yves Barral, Matthias Peter, Wilhelm Gruissem, Peter Bühlmann BMC Systems Biology 2008, 2:3 (14 January 2008)

Commentary   Open Access

Genetic interactions: the missing links for a better understanding of cancer susceptibility, progression and treatment

Christopher A Maxwell, Víctor Moreno, Xavier Solé, Laia Gómez, Pilar Hernández, Ander Urruticoechea, Miguel Pujana Molecular Cancer 2008, 7:4 (10 January 2008)

Method   Open Access Highly Accessed

Broad network-based predictability of Saccharomyces cerevisiae gene loss-of-function phenotypes

Kriston L McGary, Insuk Lee, Edward M Marcotte Genome Biology 2007, 8:R258 (5 December 2007)

Loss-of-function phenotypes of yeast genes can be predicted from the loss-of-function phenotypes of their neighbours in functional gene networks. This could potentially be applied to the prediction of human disease genes.

Review   Open Access Highly Accessed

Inferring cellular networks – a review

Florian Markowetz, Rainer Spang BMC Bioinformatics 2007, 8(Suppl 6):S5 (27 September 2007)

Method   Open Access

InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale

Haidong Wang, Eran Segal, Asa Ben-Hur, Qian-Ru Li, Marc Vidal, Daphne Koller Genome Biology 2007, 8:R192 (14 September 2007)

InSite is a computational method that integrates high-throughput protein and sequence data to infer the specific binding regions of interacting protein pairs.

Research article   Open Access Highly Accessed

Probabilistic prediction and ranking of human protein-protein interactions

Michelle S Scott, Geoffrey J Barton BMC Bioinformatics 2007, 8:239 (5 July 2007)

Research article   Open Access

A direct comparison of protein interaction confidence assignment schemes

Silpa Suthram, Tomer Shlomi, Eytan Ruppin, Roded Sharan, Trey Ideker BMC Bioinformatics 2006, 7:360 (26 July 2006)

Research article   Open Access Highly Accessed

Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae

Teresa Reguly, Ashton Breitkreutz, Lorrie Boucher, Bobby-Joe Breitkreutz, Gary C Hon, Chad L Myers, Ainslie Parsons, Helena Friesen, Rose Oughtred, Amy Tong, Chris Stark, Yuen Ho, David Botstein, Brenda Andrews, Charles Boone, Olga G Troyanskya, Trey Ideker, Kara Dolinski, Nizar N Batada, Mike Tyers Journal of Biology 2006, 5:11 (8 June 2006)

A new literature-based yeast database documents over 33,000 biological interactions, manually curated from the primary literature, and provides an invaluable resource to benchmark high-throughput methods in the study of complex networks.