Evidence map›Paper›PMID 33028629›Full record

ArticleG3 (Bethesda, Md.)2020

BioLitMine: Advanced Mining of Biomedical and Biological Literature About Human Genes and Genes from Major Model Organisms.

Yanhui Hu, Verena Chung, Aram Comjean, Jonathan Rodiger, Fnu Nipun, Norbert Perrimon, Stephanie E Mohr

Open access · goldAbstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.7field-weighted citation impact, top 32% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 16 citations in OpenAlex.

  1. Germline whole-exome sequencing revealsJournal for immunotherapy of cancer · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Yanhui HuDepartment of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115 claire_hu@genetics.med.harvard.edu.ORCID 0000-0003-1494-1402
Verena ChungDepartment of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115.ORCID 0000-0002-5622-7998
Aram ComjeanDepartment of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115.
Jonathan RodigerDepartment of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115.
Fnu NipunDepartment of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115.
Norbert PerrimonDepartment of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115.
Stephanie E MohrDepartment of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115.ORCID 0000-0001-9639-7708
Harvard University · USHoward Hughes Medical Institute · US

Funding

VectorP30CA006516 · NCI · DANA-FARBER CANCER INSTITUTE · PI JENNIFER W MACK · 1985 to 2026
$330.6M
Functional genomics resources for the Drosophila - TR&D3P41GM132087 · NIGMS · HARVARD MEDICAL SCHOOL · PI PERRIMON, NORBERT · 2019 to 2023
$6.8M
Howard Hughes Medical InstituteNCI NIH HHS P30 CA006516NIGMS NIH HHS P41 GM132087
6 · The paper itself

Abstract

The accumulation of biological and biomedical literature outpaces the ability of most researchers and clinicians to stay abreast of their own immediate fields, let alone a broader range of topics. Although available search tools support identification of relevant literature, finding relevant and key publications is not always straightforward. For example, important publications might be missed in searches with an official gene name due to gene synonyms. Moreover, ambiguity of gene names can result in retrieval of a large number of irrelevant publications. To address these issues and help researchers and physicians quickly identify relevant publications, we developed BioLitMine, an advanced literature mining tool that takes advantage of the medical subject heading (MeSH) index and gene-to-publication annotations already available for PubMed literature. Using BioLitMine, a user can identify what MeSH terms are represented in the set of publications associated with a given gene of the interest, or start with a term and identify relevant publications. Users can also use the tool to find co-cited genes and a build a literature co-citation network. In addition, BioLitMine can help users build a gene list relevant to a MeSH term, such as a list of genes relevant to "stem cells" or "breast neoplasms." Users can also start with a gene or pathway of interest and identify authors associated with that gene or pathway, a feature that makes it easier to identify experts who might serve as collaborators or reviewers. Altogether, BioLitMine extends the value of PubMed-indexed literature and its existing expert curation by providing a robust and gene-centric approach to retrieval of relevant information.

Indexed as

Medical Subject HeadingsPublicationsData MiningHumansMolecular Sequence AnnotationPubMedCo-citation networkEnrichment analysisLiterature miningModel organismsPubmed derivatives

Identifiers

PMID33028629
PMCPMC7718760
OpenAlexW3092260431

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.