ArticleBMC medical informatics and decision making2011
GenDrux: a biomedical literature search system to identify gene expression-based drug sensitivity in breast cancer.
Article in BMC medical informatics and decision making, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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.
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Who cites it
3 citing papers in PubMed.
- Automated knowledge extraction from polymer literature using natural language processing.iScience · 2021Article
- Mining the pharmacogenomics literature--a survey of the state of the art.Briefings in bioinformatics · 2012Article
- An eUtils toolset and its use for creating a pipeline to link genomics and proteomics analyses to domain-specific biomedical literature.Journal of clinical bioinformatics · 2012Article
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Authors and funding
5 authors.
Funding
Abstract
backgroundThis paper describes the development of a web-based tool, GenDrux, which extracts and presents (over the Internet) information related to the disease-gene-drug nexus. This information is archived from the relevant biomedical literature using automated methods. GenDrux is designed to alleviate the difficulties of manually processing the vast biomedical literature to identify disease-gene-drug relationships. GenDrux will evolve with the literature without additional algorithmic modifications.
resultsGenDrux, a pilot system, is developed in the domain of breast cancer and can be accessed at http://www.microarray.uab.edu/drug_gene.pl. GenDrux can be queried based on drug, gene and/or disease name. From over 8,000 relevant abstracts from the biomedical literature related to breast cancer, we have archived a corpus of more than 4,000 articles that depict gene expression-drug activity relationships for breast cancer and related cancers. The archiving process has been automated.
conclusionsThe successful development, implementation, and evaluation of this and similar systems when created may provide clinicians with a tool for literature management, clinical decision making, thus setting the platform for personalized therapy in the future.
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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.