ArticleBMC bioinformatics2017
Comparison of statistical methods for subnetwork detection in the integration of gene expression and protein interaction network.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- GAMclust: identification of regulated metabolic modules in bulk, single cell and spatial gene expression data.Bioinformatics (Oxford, England) · 2026Article
- A network embedding approach to identify active modules in biological interaction networks.Life science alliance · 2023Article
- NetMix: A Network-Structured Mixture Model for Reduced-Bias Estimation of Altered Subnetworks.Journal of computational biology : a journal of computational molecular cell biology · 2021Article
- Mapping Transcriptome Data to Protein-Protein Interaction Networks of Inflammatory Bowel Diseases Reveals Disease-Specific Subnetworks.Frontiers in genetics · 2021Article
- DOMINO: a network-based active module identification algorithm with reduced rate of false calls.Molecular systems biology · 2021Article
- Article
- Finding disease modules for cancer and COVID-19 in gene co-expression networks with the Core&Peel method.Scientific reports · 2020Article
- NetCore: a network propagation approach using node coreness.Nucleic acids research · 2020Article
- Enhancing reproducibility of gene expression analysis with known protein functional relationships: The concept of well-associated protein.PLoS computational biology · 2020Article
- Investigating the deregulation of metabolic tasks via Minimum Network Enrichment Analysis (MiNEA) as applied to nonalcoholic fatty liver disease using mouse and human omics data.PLoS computational biology · 2019Article
- Differentially mutated subnetworks discovery.Algorithms for molecular biology : AMB · 2019Article
- A Comprehensive Survey of Tools and Software for Active Subnetwork Identification.Frontiers in genetics · 2019Review
- Defining a Characteristic Gene Expression Set Responsible for Cancer Stem Cell-Like Features in a Sub-Population of Ewing Sarcoma Cells CADO-ES1.International journal of molecular sciences · 2018Article
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5 authors.
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Abstract
backgroundWith the advancement of high-throughput technologies and enrichment of popular public databases, more and more research focuses of bioinformatics research have been on computational integration of network and gene expression profiles for extracting context-dependent active subnetworks. Many methods for subnetwork searching have been developed. Scoring and searching algorithms present a range of computational considerations and implementations. The primary goal of present study is to comprehensively evaluate the performance of different subnetwork detection methods. Eleven popular methods were selected for comprehensive comparison.
resultsFirst, taking into account the dependence of genes given a protein-protein interaction (PPI) network, we simulated microarray gene expression data under case and control conditions. Then each method was applied to the simulated data for subnetwork identification. Second, a large microarray data set of prostate cancer was used to assess the practical performance of each method. Using both simulation studies and a real data application, we evaluated the performance of different methods in terms of recall and precision.
conclusionsjActiveModules, PinnacleZ and WMAXC performed well in identifying subnetwork with relative high precision and recall. BioNet performed very well only in precision. As none of methods outperformed other methods overall, users should choose an appropriate method based on the purposes of their studies.
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