ArticleJournal of chemical information and modeling2018
Chemotext: A Publicly Available Web Server for Mining Drug-Target-Disease Relationships in PubMed.
Article in Journal of chemical information and modeling, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed.
- AI-Driven Discovery and BSL-4 Validation of Cross-Filovirus Ebola-Marburg Inhibitors and their Synergistic Combinations.bioRxiv : the preprint server for biology · 2026Article
- Breaking the Phalanx: Overcoming Bacterial Drug Resistance with Quorum Sensing Inhibitors that Enhance Therapeutic Activity of Antibiotics.bioRxiv : the preprint server for biology · 2025Article
- AI-driven discovery of synergistic drug combinations against pancreatic cancer.Nature communications · 2025Article
- Drug repurposing based on the DTD-GNN graph neural network: revealing the relationships among drugs, targets and diseases.BMC genomics · 2024Article
- Praemonitus praemunitus: can we forecast and prepare for future viral disease outbreaks?FEMS microbiology reviews · 2023Review
- Advancement of Computational Design Drug Delivery System in COVID-19: Current Updates and Future Crosstalk- A Critical update.Infectious disorders drug targets · 2023Article
- e-TSN: an interactive visual exploration platform for target-disease knowledge mapping from literature.Briefings in bioinformatics · 2022Article
- Chemical named entity recognition in the texts of scientific publications using the naïve Bayes classifier approach.Journal of cheminformatics · 2022Article
- Knowledge-based approaches to drug discovery for rare diseases.Drug discovery today · 2022Review
- STopTox: AnEnvironmental health perspectives · 2022Article
- Integration of Transcriptomics Data and Metabolomic Data Using Biomedical Literature Mining and Pathway Analysis.Methods in molecular biology (Clifton, N.J.) · 2022Article
- An Integrative Heterogeneous Graph Neural Network-Based Method for Multi-Labeled Drug Repurposing.Frontiers in pharmacology · 2022Article
- A chronicle review of new techniques that facilitate the understanding and development of optimal individualized therapeutic strategies for chordoma.Frontiers in oncology · 2022Review
- A critical overview of computational approaches employed for COVID-19 drug discovery.Chemical Society reviews · 2021Review
- Synergistic and Antagonistic Drug Combinations against SARS-CoV-2.Molecular therapy : the journal of the American Society of Gene Therapy · 2021Article
- Using Bibliometric Analysis and Machine Learning to Identify Compounds Binding to Sialidase-1.ACS omega · 2021Article
- An omics perspective on drug target discovery platforms.Briefings in bioinformatics · 2020Article
- Discovery of Synergistic and Antagonistic Drug Combinations against SARS-CoV-2 In Vitro.bioRxiv : the preprint server for biology · 2020Article
- Data and Text Mining Help Identify Key Proteins Involved in the Molecular Mechanisms Shared by SARS-CoV-2 and HIV-1.Molecules (Basel, Switzerland) · 2020Article
- Automated Extraction of Information From Texts of Scientific Publications: Insights Into HIV Treatment Strategies.Frontiers in genetics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Elucidation of the mechanistic relationships between drugs, their targets, and diseases is at the core of modern drug discovery research. Thousands of studies relevant to the drug-target-disease (DTD) triangle have been published and annotated in the Medline/PubMed database. Mining this database affords rapid identification of all published studies that confirm connections between vertices of this triangle or enable new inferences of such connections. To this end, we describe the development of Chemotext, a publicly available Web server that mines the entire compendium of published literature in PubMed annotated by Medline Subject Heading (MeSH) terms. The goal of Chemotext is to identify all known DTD relationships and infer missing links between vertices of the DTD triangle. As a proof-of-concept, we show that Chemotext could be instrumental in generating new drug repurposing hypotheses or annotating clinical outcomes pathways for known drugs. The Chemotext Web server is freely available at http://chemotext.mml.unc.edu .
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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.