Fernando Sola, Daniel Ayala, Marina Pulido, Rafael Ayala, Lorena López-Cerero, Inma Hernández, David Ruiz
{"title":"ginmappeR: an unified approach for integrating gene and protein identifiers across biological sequence databases.","authors":"Fernando Sola, Daniel Ayala, Marina Pulido, Rafael Ayala, Lorena López-Cerero, Inma Hernández, David Ruiz","doi":"10.1093/bioadv/vbae129","DOIUrl":null,"url":null,"abstract":"<p><strong>Summary: </strong>The proliferation of biological sequence data, due to developments in molecular biology techniques, has led to the creation of numerous open access databases on gene and protein sequencing. However, the lack of direct equivalence between identifiers across these databases difficults data integration. To address this challenge, we introduce <i>ginmappeR</i>, an integrated R package facilitating the translation of gene and protein identifiers between databases. By providing a unified interface, <i>ginmappeR</i> streamlines the integration of diverse data sources into biological workflows, so it enhances efficiency and user experience.</p><p><strong>Availability and implementation: </strong>from Bioconductor: https://bioconductor.org/packages/ginmappeR.</p>","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11387618/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics advances","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioadv/vbae129","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Summary: The proliferation of biological sequence data, due to developments in molecular biology techniques, has led to the creation of numerous open access databases on gene and protein sequencing. However, the lack of direct equivalence between identifiers across these databases difficults data integration. To address this challenge, we introduce ginmappeR, an integrated R package facilitating the translation of gene and protein identifiers between databases. By providing a unified interface, ginmappeR streamlines the integration of diverse data sources into biological workflows, so it enhances efficiency and user experience.
Availability and implementation: from Bioconductor: https://bioconductor.org/packages/ginmappeR.