Computational prediction of promotors in Agrobacterium tumefaciens strain C58 by using the machine learning technique.

ABSTRACT: Promotors are those genomic regions on the upstream of genes, which are bound by RNA polymerase for starting gene transcription. Because it is the most critical element of gene expression, the recognition of promoters is crucial to understand the regulation of gene expression. This study aimed to develop a machine learning-based model to predict promotors in Agrobacterium tumefaciens (A. tumefaciens) strain C58. In the model, promotor sequences were encoded by three different kinds of feature descriptors, namely, accumulated nucleotide frequency, k-mer nucleotide composition, and binary encodings. The obtained features were optimized by using correlation and the mRMR-based algorithm. These optimized features were inputted into a random forest (RF) classifier to discrim

SUBMITTER: Zulfiqar H 

PROVIDER: S-EPMC10133480 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature