Structured RDF dataset for genomic feature extraction and detection of biotechnological microorganisms of the Burkholderia genus

The current dataset has been built from 200 genomes of <i>Burkholderia</i> genus microorganisms in GenBank Flat File (GBFF) format, with information obtained from the National Center for Biotechnology Information (NCBI). Python scripts were developed to automate the extraction of genomic features such as coding sequences (CDS) and different types of RNA, extracting the descriptive information of each one. The extracted features were transformed into RDF (Resource Description Framework) format as initial knowledge graphs with Turtle syntax, and later, they were merged into a unified knowledge graph (KG) to facilitate their access via queries written in the SPARQL system. This dataset is publicly available to researchers through the Mendeley repository, allowing them to perform complex searches, looking for composite features coming from the dataset's source organisms. Choosing the RDF format for the knowledge graph also promotes interoperability with other biological datasets that use the same structure and are widely accessible through SPARQL Endpoints.

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Publication Details

Journal
Data in Brief
Published
2025-10-10
DOI
https://doi.org/10.1016/j.dib.2025.112137
Primary Topic
Microbial Community Ecology and Physiology
Type
article
Field-Weighted Citation Impact
0.00
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article

Structured RDF dataset for genomic feature extraction and detection of biotechnological microorganisms of the Burkholderia genus

Yagul Pedraza-Pérez, Gilberto Solorza Luna, Reynold Osuna-González, Rosa María Valdovinos-Rosas
Data in Brief
Microbial Community Ecology and Physiology
article

Structured RDF dataset for genomic feature extraction and detection of biotechnological microorganisms of the Burkholderia genus

Yagul Pedraza-Pérez, Gilberto Solorza Luna, Reynold Osuna-González, Rosa María Valdovinos-Rosas
article en

Abstract

The current dataset has been built from 200 genomes of <i>Burkholderia</i> genus microorganisms in GenBank Flat File (GBFF) format, with information obtained from the National Center for Biotechnology Information (NCBI). Python scripts were developed to automate the extraction of genomic features such as coding sequences (CDS) and different types of RNA, extracting the descriptive information of each one. The extracted features were transformed into RDF (Resource Description Framework) format as initial knowledge graphs with Turtle syntax, and later, they were merged into a unified knowledge graph (KG) to facilitate their access via queries written in the SPARQL system. This dataset is publicly available to researchers through the Mendeley repository, allowing them to perform complex searches, looking for composite features coming from the dataset's source organisms. Choosing the RDF format for the knowledge graph also promotes interoperability with other biological datasets that use the same structure and are widely accessible through SPARQL Endpoints.

Data in BriefVol. 63
Universidad Autónoma del Estado de México (MX), Benemérita Universidad Autónoma de Puebla (MX)
Openalex Percentile: Top 73%
Microbial Community Ecology and Physiology
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