ArticleNucleic acids research2014
OncoSearch: cancer gene search engine with literature evidence.
Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Generalized probabilistic canonical correlation analysis for multi-modal data integration with full or partial observations.BMC bioinformatics · 2025Article
- Disentangling protein metabolic costs in human cells and tissues.PNAS nexus · 2025Article
- MetaTron: advancing biomedical annotation empowering relation annotation and collaboration.BMC bioinformatics · 2024Article
- Cancer-Alterome: a literature-mined resource for regulatory events caused by genetic alterations in cancer.Scientific data · 2024Article
- PubMed and beyond: biomedical literature search in the age of artificial intelligence.EBioMedicine · 2024Review
- Building a large gene expression-cancer knowledge base with limited human annotations.Database : the journal of biological databases and curation · 2023Article
- Article
- Inference of epigenetic subnetworks by Bayesian regression with the incorporation of prior information.Scientific reports · 2022Article
- Analysis of candidate genes expected to be essential for melanoma surviving.Cancer cell international · 2020Article
- Drug repurposing in oncology: Compounds, pathways, phenotypes and computational approaches for colorectal cancer.Biochimica et biophysica acta. Reviews on cancer · 2019Review
- BEST: Next-Generation Biomedical Entity Search Tool for Knowledge Discovery from Biomedical Literature.PloS one · 2016Article
- Constructing a molecular interaction network for thyroid cancer via large-scale text mining of gene and pathway events.BMC systems biology · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In order to identify genes that are involved in oncogenesis and to understand how such genes affect cancers, abnormal gene expressions in cancers are actively studied. For an efficient access to the results of such studies that are reported in biomedical literature, the relevant information is accumulated via text-mining tools and made available through the Web. However, current Web tools are not yet tailored enough to allow queries that specify how a cancer changes along with the change in gene expression level, which is an important piece of information to understand an involved gene's role in cancer progression or regression. OncoSearch is a Web-based engine that searches Medline abstracts for sentences that mention gene expression changes in cancers, with queries that specify (i) whether a gene expression level is up-regulated or down-regulated, (ii) whether a certain type of cancer progresses or regresses along with such gene expression change and (iii) the expected role of the gene in the cancer. OncoSearch is available through http://oncosearch.biopathway.org.
Indexed as
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.