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Bacillus subtilis promoter sequences data set for promoter prediction in Gram-positive bacteria
- Source :
- Data in Brief, Vol 19, Iss, Pp 264-270 (2018), Data in Brief
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- This paper presents a prediction of Bacillus subtilis promoters using a Support Vector Machine system. In the literature, there is a lack of information on Gram-positive bacterial promoter sequences compared to Gram-negative bacteria. Promoter sequence identification is essential for studying gene expression. Initially, we collected the B. subtilis genome sequence from the NCBI database, and promoters were identified by their sigma factors in the DBTBS database. We then grouped the promoters according to 15 factors in 2 domains, corresponding to sigma 54 and sigma 70 of Gram-negative bacteria. Based on these data we developed a script in Python to search for promoters in the B. subtilis genome. After processing the data, we obtained 767 promoter sequences for B. subtilis, most of which were recognized by sigma SigA. To validate the data we found, we developed a software package called BacSVM+, which receives promoters as input and returns the best combination of parameters in a LibSVM library to predict promoter regions in the bacteria used in the simulation. All data gathered as well as the BacSVM+ software is available for download at http://bacpp.bioinfoucs.com/rafael/Sigmas.zip. Keywords: Promoter sequences, Bacillus subtilis, SVM
- Subjects :
- 0301 basic medicine
Whole genome sequencing
Genetics, Genomics and Molecular Biology
Multidisciplinary
030102 biochemistry & molecular biology
biology
SVM
Promoter sequences
Sigma
Promoter
Computational biology
Bacillus subtilis
lcsh:Computer applications to medicine. Medical informatics
biology.organism_classification
Genome
03 medical and health sciences
030104 developmental biology
Sigma factor
Gene expression
lcsh:R858-859.7
lcsh:Science (General)
Bacteria
lcsh:Q1-390
Subjects
Details
- ISSN :
- 23523409
- Volume :
- 19
- Database :
- OpenAIRE
- Journal :
- Data in Brief
- Accession number :
- edsair.doi.dedup.....0bae98254d9fcc9ef15eddab4ba3c5ce