ArticleJournal of biomedical informatics2010
Mining connections between chemicals, proteins, and diseases extracted from Medline annotations.
Article in Journal of biomedical informatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed, 64 citations in OpenAlex.
- Article
- Knowledge-based approaches to drug discovery for rare diseases.Drug discovery today · 2022Review
- "In Litero" Screening: Retrospective Evaluation of Clinical Evidence to Establish a Reference List of Human Chemical Respiratory Sensitizers.Frontiers in toxicology · 2022Article
- Using Bibliometric Analysis and Machine Learning to Identify Compounds Binding to Sialidase-1.ACS omega · 2021Article
- A cross-platform approach to characterize and screen potential neurovascular unit toxicants.Reproductive toxicology (Elmsford, N.Y.) · 2020Article
- Characterizing cleft palate toxicants using ToxCast data, chemical structure, and the biomedical literature.Birth defects research · 2020Article
- Article
- Article
- A bibliometric review of drug repurposing.Drug discovery today · 2018Review
- Chemotext: A Publicly Available Web Server for Mining Drug-Target-Disease Relationships in PubMed.Journal of chemical information and modeling · 2018Article
- QSAR models of human data can enrich or replace LLNA testing for human skin sensitization.Green chemistry : an international journal and green chemistry resource : GC · 2016Article
- Cheminformatics-aided pharmacovigilance: application to Stevens-Johnson Syndrome.Journal of the American Medical Informatics Association : JAMIA · 2016Article
- Analysis of PubMed User Sessions Using a Full-Day PubMed Query Log: A Comparison of Experienced and Nonexperienced PubMed Users.JMIR medical informatics · 2015Article
- Big data in chemical toxicity research: the use of high-throughput screening assays to identify potential toxicants.Chemical research in toxicology · 2014Review
- Chemical named entities recognition: a review on approaches and applications.Journal of cheminformatics · 2014Review
- Integrative approaches for predicting in vivo effects of chemicals from their structural descriptors and the results of short-term biological assays.Current topics in medicinal chemistry · 2014Review
- Evaluating gold standard corpora against gene/protein tagging solutions and lexical resources.Journal of biomedical semantics · 2013Article
- A computational model predicting disruption of blood vessel development.PLoS computational biology · 2013Article
- A study on PubMed search tag usage pattern: association rule mining of a full-day PubMed query log.BMC medical informatics and decision making · 2013Article
- Mining the pharmacogenomics literature--a survey of the state of the art.Briefings in bioinformatics · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
The biomedical literature is an important source of information about the biological activity and effects of chemicals. We present an application that extracts terms indicating biological activity of chemicals from Medline records, associates them with chemical name and stores the terms in a repository called ChemoText. We describe the construction of ChemoText and then demonstrate its utility in drug research by employing Swanson's ABC discovery paradigm. We reproduce Swanson's discovery of a connection between magnesium and migraine in a novel approach that uses only proteins as the intermediate B terms. We validate our methods by using a cutoff date and evaluate them by calculating precision and recall. In addition to magnesium, we have identified valproic acid and nitric oxide as chemicals which developed links to migraine. We hypothesize, based on protein annotations, that zinc and retinoic acid may play a role in migraine. The ChemoText repository has promise as a data source for drug discovery.
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.