ABSTRACT: BACKGROUND: Functional analyses of genomic data within the context of a priori biomolecular networks cangive valuable mechanistic insights. However, such analyses are not a trivial task, owing to thecomplexity of biological networks and lack of computational methods for their effectiveintegration with experimental data. RESULTS: We developed a software application suite, NetWalker, as a one-stop platform featuring anumber of novel holistic (i.e. assesses the whole data distribution without requiring datacutoffs) data integration and analysis methods for network-based comparative interpretationsof genome-scale data. The central analysis components, NetWalk and FunWalk, are novel random walk-based network analysis methods that provide unique analysis capabilities toassess the entire data distributions together with network connectivity to prioritize molecularand functional networks, respectively, most highlighted in the supplied data. Extensive interoperabilitybetween the analysis components and with external applications, including R,adds to the flexibility of data analyses. Here, we present a detailed computational analysis ofour microarray gene expression data from MCF7 cells treated with lethal and sublethal dosesof doxorubicin. CONCLUSION: NetWalker, a detailed step-by-step tutorial containing the analyses presented in this paper anda manual are available at the web site http://netwalkersuite.org.
Komurov, K., Dursun, S., Erdin, S., & Ram, P. T. (2012). NetWalker: A contextual network analysis tool for functional genomics. BMC Genomics, 13(1). https://doi.org/10.1186/1471-2164-13-282