ArticlePloS one2014
Automatic context-specific subnetwork discovery from large interaction networks.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Identification of Diagnostic and Prognostic Subnetwork Biomarkers for Women with Breast Cancer Using Integrative Genomic and Network-Based Analysis.International journal of molecular sciences · 2024Article
- CONFIGURE: A pipeline for identifying context specific regulatory modules from gene expression data and its application to breast cancer.BMC medical genomics · 2019Article
- Evidence of perturbations of the cytokine network in preterm labor.American journal of obstetrics and gynecology · 2015Article
- ModuleBlast: identifying activated sub-networks within and across species.Nucleic acids research · 2015Article
- iCOSSY: An Online Tool for Context-Specific Subnetwork Discovery from Gene Expression Data.PloS one · 2015Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Genes act in concert via specific networks to drive various biological processes, including progression of diseases such as cancer. Under different phenotypes, different subsets of the gene members of a network participate in a biological process. Single gene analyses are less effective in identifying such core gene members (subnetworks) within a gene set/network, as compared to gene set/network-based analyses. Hence, it is useful to identify a discriminative classifier by focusing on the subnetworks that correspond to different phenotypes. Here we present a novel algorithm to automatically discover the important subnetworks of closely interacting molecules to differentiate between two phenotypes (context) using gene expression profiles. We name it COSSY (COntext-Specific Subnetwork discoverY). It is a non-greedy algorithm and thus unlikely to have local optima problems. COSSY works for any interaction network regardless of the network topology. One added benefit of COSSY is that it can also be used as a highly accurate classification platform which can produce a set of interpretable features.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.