Evidence map›Paper›PMID 38565273›Full record

ArticleBioinformatics (Oxford, England)2024

3Dmapper: a command line tool for BioBank-scale mapping of variants to protein structures.

Victoria Ruiz-Serra, Samuel Valentini, Sergi Madroñero, Alfonso Valencia, Eduard Porta-Pardo

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Victoria Ruiz-SerraBarcelona Supercomputing Center (BSC).ORCID 0000-0003-3991-0514
Samuel ValentiniDepartment of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento 38123, Italy.
Sergi MadroñeroJosep Carreras Leukaemia Research Institute (IJC), Badalona 08916, Spain.
Alfonso ValenciaBarcelona Supercomputing Center (BSC).
Eduard Porta-PardoBarcelona Supercomputing Center (BSC).ORCID 0000-0001-7900-4239

Funding

La Caixa Junior Leader Fellowship LCF/BQ/PI18/11630003Spanish Ministry of Science RYC2019-026415-I
6 · The paper itself

Abstract

motivationThe interpretation of genomic data is crucial to understand the molecular mechanisms of biological processes. Protein structures play a vital role in facilitating this interpretation by providing functional context to genetic coding variants. However, mapping genes to proteins is a tedious and error-prone task due to inconsistencies in data formats. Over the past two decades, numerous tools and databases have been developed to automatically map annotated positions and variants to protein structures. However, most of these tools are web-based and not well-suited for large-scale genomic data analysis.

resultsTo address this issue, we introduce 3Dmapper, a stand-alone command-line tool developed in Python and R. It systematically maps annotated protein positions and variants to protein structures, providing a solution that is both efficient and reliable. AVAILABILITY AND IMPLEMENTATION: https://github.com/vicruiser/3Dmapper.

Indexed as

Biological Specimen BanksSoftwareGenomicsProteinsProteins

Identifiers

PMID38565273
PMCPMC11018535

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.