Evidence map›Paper›PMID 33763309›Full record

ArticlePeerJ2021

pmparser and PMDB: resources for large-scale, open studies of the biomedical literature.

Joshua L Schoenbachler, Jacob J Hughey

Abstract read
In one paragraph

Article in PeerJ, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Joshua L SchoenbachlerDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.ORCID 0000-0001-8544-6359
Jacob J HugheyDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.ORCID 0000-0002-1558-6089

Funding

A Multi-scale Approach to the Mammalian Circadian System and Its Role in Human Health and Disease - Administrative SupplementR35GM124685 · NIGMS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI HUGHEY, JACOB J · 2017 to 2021
$2.1M
NIGMS NIH HHS R35 GM124685
6 · The paper itself

Abstract

PubMed is an invaluable resource for the biomedical community. Although PubMed is freely available, the existing API is not designed for large-scale analyses and the XML structure of the underlying data is inconvenient for complex queries. We developed an R package called pmparser to convert the data in PubMed to a relational database. Our implementation of the database, called PMDB, currently contains data on over 31 million PubMed Identifiers (PMIDs) and is updated regularly. Together, pmparser and PMDB can enable large-scale, reproducible, and transparent analyses of the biomedical literature. pmparser is licensed under GPL-2 and available at https://pmparser.hugheylab.org. PMDB is available in both PostgreSQL (DOI 10.5281/zenodo.4008109) and Google BigQuery (https://console.cloud.google.com/bigquery?project=pmdb-bq&d=pmdb).

Indexed as

DatabaseParsingPublishingPubmed

Identifiers

PMID33763309
PMCPMC7955988

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.