ArticleJournal of biomedical semantics2015
Linking gene expression to phenotypes via pathway information.
Article in Journal of biomedical semantics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- Characterizing diseases using genetic and clinical variables: A data analytics approach.Quantitative biology (Beijing, China) · 2024Article
- Pathway level subtyping identifies a slow-cycling biological phenotype associated with poor clinical outcomes in colorectal cancer.Nature genetics · 2024Article
- Unravelling the Impact of Cyclic Mechanical Stretch in Keratoconus-A Transcriptomic Profiling Study.International journal of molecular sciences · 2023Article
- Muscle transcriptome analysis provides new insights into the growth gap between fast- and slow-growingFrontiers in genetics · 2023Article
- PhenCards: a data resource linking human phenotype information to biomedical knowledge.Genome medicine · 2021Article
- GOcats: A tool for categorizing Gene Ontology into subgraphs of user-defined concepts.PloS one · 2020Article
- Progress in data interoperability to support computational toxicology and chemical safety evaluation.Toxicology and applied pharmacology · 2019Review
- Muscle transcriptome resource for growth, lipid metabolism and immune system in Hilsa shad, Tenualosa ilisha.Genes & genomics · 2019Article
- Novel application of normalized pointwise mutual information (NPMI) to mine biomedical literature for gene sets associated with disease: use case in breast carcinogenesis.Computational toxicology (Amsterdam, Netherlands) · 2018Article
- An epigenetic basis for an omnigenic model of psychiatric disorders.Journal of theoretical biology · 2018Review
- Gene ORGANizer: linking genes to the organs they affect.Nucleic acids research · 2017Article
- The digital revolution in phenotyping.Briefings in bioinformatics · 2016Article
- Molecular studies of phenotype variation in canine RPGR-XLPRA1.Molecular vision · 2016Article
- Special issue on bio-ontologies and phenotypes.Journal of biomedical semantics · 2015Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Establishing robust links among gene expression, pathways and phenotypes is critical for understanding diseases and developing treatments. In recent years there have been many efforts to develop the computational means to traverse from genes to gene expression, model pathways and classify phenotypes. Numerous ontologies and other controlled vocabularies have been developed, as well as computational methods to combine and mine these data sets and establish connections. Here we discuss these efforts and identify areas of future work that could lead to a better integration of genes, pathways and phenotypes to provide insights into the mechanisms under which gene mutations affect expression and pathways and how these effects are manifested onto the phenotype.
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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.