GeNeCK: a web server for gene network construction and visualization

BMC Bioinformatics

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[1] 0000 0000 9482 7121, grid.267313.2, BioHPC team, Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, Texas, United States;0000 0000 9482 7121, grid.267313.2, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., 75390, Dallas, TX, United States;0000 0000 9482 7121, grid.267313.2, Department of Clinical Sciences, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, Texas, United States;0000 0000 9482 7121, grid.267313.2, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., 75390, Dallas, TX, United States;0000 0000 9482 7121, grid.267313.2, Department of Clinical Sciences, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, Texas, United States;0000 0000 9482 7121, grid.267313.2, Harold C. Simmons Cancer Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., 75390, Dallas, Texas, United States;0000 0001 2364 8385, grid.202119.9, Department of Statistics, Inha University, Incheon, South Korea;

关键词: Gene network;    Gene network;    Statistical method;    Web server;    Correlation;    Likelihood;    Bayesian;    Mutual information;    Ensemble;    Hub gene;    Visualization;   

DOI  :  10.1186/s12859-018-2560-0

来源: publisher

【 摘 要 】

BackgroundReverse engineering approaches to infer gene regulatory networks using computational methods are of great importance to annotate gene functionality and identify hub genes. Although various statistical algorithms have been proposed, development of computational tools to integrate results from different methods and user-friendly online tools is still lagging.ResultsWe developed a web server that efficiently constructs gene networks from expression data. It allows the user to use ten different network construction methods (such as partial correlation-, likelihood-, Bayesian- and mutual information-based methods) and integrates the resulting networks from multiple methods. Hub gene information, if available, can be incorporated to enhance performance.ConclusionsGeNeCK is an efficient and easy-to-use web application for gene regulatory network construction. It can be accessed at http://lce.biohpc.swmed.edu/geneck.

【 授权许可】

CC BY