ArticleBioinformatics (Oxford, England)2016
HiPub: translating PubMed and PMC texts to networks for knowledge discovery.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- PubMed knowledge graph 2.0: Connecting papers, patents, and clinical trials in biomedical science.Scientific data · 2025Article
- PubTator central: automated concept annotation for biomedical full text articles.Nucleic acids research · 2019Article
- deepBioWSD: effective deep neural word sense disambiguation of biomedical text data.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Translating cancer genomics into precision medicine with artificial intelligence: applications, challenges and future perspectives.Human genetics · 2019Review
- Tool for filtering PubMed search results by sample size.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Deep learning of mutation-gene-drug relations from the literature.BMC bioinformatics · 2018Article
- Signalling maps in cancer research: construction and data analysis.Database : the journal of biological databases and curation · 2018Article
- Searching for Clinically Relevant Biomarkers in Geriatric Oncology.BioMed research international · 2018Review
- Rapid and Reusable Text Visualization and Exploration Development with DELVE.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2017Article
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
unlabelledWe introduce HiPub, a seamless Chrome browser plug-in that automatically recognizes, annotates and translates biomedical entities from texts into networks for knowledge discovery. Using a combination of two different named-entity recognition resources, HiPub can recognize genes, proteins, diseases, drugs, mutations and cell lines in texts, and achieve high precision and recall. HiPub extracts biomedical entity-relationships from texts to construct context-specific networks, and integrates existing network data from external databases for knowledge discovery. It allows users to add additional entities from related articles, as well as user-defined entities for discovering new and unexpected entity-relationships. HiPub provides functional enrichment analysis on the biomedical entity network, and link-outs to external resources to assist users in learning new entities and relations. AVAILABILITY AND IMPLEMENTATION: HiPub and detailed user guide are available at http://hipub.korea.ac.kr CONTACT: kangj@korea.ac.kr, aikchoon.tan@ucdenver.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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.