ArticleJournal of cheminformatics2010
WENDI: A tool for finding non-obvious relationships between compounds and biological properties, genes, diseases and scholarly publications.
Article in Journal of cheminformatics, 2010. 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
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
8 citing papers in PubMed.
- USR-VS: a web server for large-scale prospective virtual screening using ultrafast shape recognition techniques.Nucleic acids research · 2016Article
- Site of reactivity models predict molecular reactivity of diverse chemicals with glutathione.Chemical research in toxicology · 2015Article
- First steps towards semantic descriptions of electronic laboratory notebook records.Journal of cheminformatics · 2013Article
- Cheminformatics and the Semantic Web: adding value with linked data and enhanced provenance.Wiley interdisciplinary reviews. Computational molecular science · 2013Article
- Metab2MeSH: annotating compounds with medical subject headings.Bioinformatics (Oxford, England) · 2012Article
- Why open drug discovery needs four simple rules for licensing data and models.PLoS computational biology · 2012Article
- ChemMine tools: an online service for analyzing and clustering small molecules.Nucleic acids research · 2011Article
- Semantic inference using chemogenomics data for drug discovery.BMC bioinformatics · 2011Article
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
backgroundIn recent years, there has been a huge increase in the amount of publicly-available and proprietary information pertinent to drug discovery. However, there is a distinct lack of data mining tools available to harness this information, and in particular for knowledge discovery across multiple information sources. At Indiana University we have an ongoing project with Eli Lilly to develop web-service based tools for integrative mining of chemical and biological information. In this paper, we report on the first of these tools, called WENDI (Web Engine for Non-obvious Drug Information) that attempts to find non-obvious relationships between a query compound and scholarly publications, biological properties, genes and diseases using multiple information sources.
resultsWe have created an aggregate web service that takes a query compound as input, calls multiple web services for computation and database search, and returns an XML file that aggregates this information. We have also developed a client application that provides an easy-to-use interface to this web service. Both the service and client are publicly available.
conclusionsInitial testing indicates this tool is useful in identifying potential biological applications of compounds that are not obvious, and in identifying corroborating and conflicting information from multiple sources. We encourage feedback on the tool to help us refine it further. We are now developing further tools based on this model.
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.