CRISPRcasIdentifier: Machine learning for accurate identification and classification of CRISPR-Cas systems.

ABSTRACT:

Background

CRISPR-Cas genes are extraordinarily diverse and evolve rapidly when compared to other prokaryotic genes. With the rapid increase in newly sequenced archaeal and bacterial genomes, manual identification of CRISPR-Cas systems is no longer viable. Thus, an automated approach is required for advancing our understanding of the evolution and diversity of these systems and for finding new candidates for genome engineering in eukaryotic models.

Results

We introduce CRISPRcasIdentifier, a new machine learning-based tool that combines regression and classification models for the prediction of potentially missing proteins in instances of CRISPR-Cas systems and the prediction of their respective subtypes. In contrast to other available tools, CRISPRcasIdentifier can both det

SUBMITTER: Padilha VA 

PROVIDER: S-EPMC7298778 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature