ArticleBioinformatics (Oxford, England)2016
PhenomeScape: a cytoscape app to identify differentially regulated sub-networks using known disease associations.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-analysis of Transcriptomic Data from Lung Autopsy and Cellular Models of SARS-CoV-2 Infection.Biochemical genetics · 2024Pooled it
- Unveiling inflammatory and prehypertrophic cell populations as key contributors to knee cartilage degeneration in osteoarthritis using multi-omics data integration.Annals of the rheumatic diseases · 2024Article
- Revealing the Modular Similarities and Differences Among Alzheimer's Disease, Vascular Dementia, and Parkinson's Disease in Genomic Networks.Neuromolecular medicine · 2022Article
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- Deciphering the scalene association among type-2 diabetes mellitus, prostate cancer, and chronic myeloid leukemia via enrichment analysis of disease-gene network.Cancer medicine · 2019Article
- The Potential Mechanism of Bufadienolide-Like Chemicals on Breast Cancer via Bioinformatics Analysis.Cancers · 2019Article
- Stratification of knee osteoarthritis: two major patient subgroups identified by genome-wide expression analysis of articular cartilage.Annals of the rheumatic diseases · 2018Article
- Subgroup analysis reveals molecular heterogeneity and provides potential precise treatment for pancreatic cancers.OncoTargets and therapy · 2018Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
PhenomeScape is a Cytoscape app which provides easy access to the PhenomeExpress algorithm to interpret gene expression data. PhenomeExpress integrates protein interaction networks with known phenotype to gene associations to find active sub-networks enriched in differentially expressed genes. It also incorporates cross-species phenotypes and associations to include results from animal models of disease. With expression data imported into PhenomeScape, the user can quickly generate and visualise interactive sub-networks. PhenomeScape thus enables researchers to use prior knowledge of a disease to identify differentially regulated sub-networks and to generate an overview of altered biologically processes specific to that disease. AVAILABILITY AND IMPLEMENTATION: Freely available for download at https://github.com/soulj/PhenomeScape CONTACT: jamie.soul@postgrad.manchester.ac.uk or jean-marc.schwartz@manchester.ac.uk.
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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.