ArticleGenome medicine2015
Inferring pathway dysregulation in cancers from multiple types of omic data.
Article in Genome medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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
8 citing papers in PubMed, 13 citations in OpenAlex.
- Metabolic signature ofFrontiers in veterinary science · 2023Article
- A comprehensive survey of the approaches for pathway analysis using multi-omics data integration.Briefings in bioinformatics · 2022Review
- ReactomeGSA - Efficient Multi-Omics Comparative Pathway Analysis.Molecular & cellular proteomics : MCP · 2020Article
- Uncovering biomarker genes with enriched classification potential from Hallmark gene sets.Scientific reports · 2019Article
- Mathematical modeling and computational prediction of cancer drug resistance.Briefings in bioinformatics · 2018Review
- Window-of-Opportunity Study of Valproic Acid in Breast Cancer Testing a Gene Expression Biomarker.JCO precision oncology · 2017Article
- Practical aspects of NGS-based pathways analysis for personalized cancer science and medicine.Oncotarget · 2016Review
- Integrative analyses reveal signaling pathways underlying familial breast cancer susceptibility.Molecular systems biology · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although in some cases individual genomic aberrations may drive disease development in isolation, a complex interplay among multiple aberrations is common. Accordingly, we developed Gene Set Omic Analysis (GSOA), a bioinformatics tool that can evaluate multiple types and combinations of omic data at the pathway level. GSOA uses machine learning to identify dysregulated pathways and improves upon other methods because of its ability to decipher complex, multigene patterns. We compare GSOA to alternative methods and demonstrate its ability to identify pathways known to play a role in various cancer phenotypes. Software implementing the GSOA method is freely available from https://bitbucket.org/srp33/gsoa.
Identifiers
What OpenQuestion holds
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.