Genomic style: yet another deep-learning approach to characterize bacterial genome sequences.

ABSTRACT:

Motivation

Biological sequence classification is the most fundamental task in bioinformatics analysis. For example, in metagenome analysis, binning is a typical type of DNA sequence classification. In order to classify sequences, it is necessary to define sequence features. The k-mer frequency, base composition and alignment-based metrics are commonly used. On the other hand, in the field of image recognition using machine learning, image classification is broadly divided into those based on shape and those based on style. A style matrix was introduced as a method of expressing the style of an image (e.g. color usage and texture).

Results

We propose a novel sequence feature, called genomic style, inspired by image classification approaches, for classifying and cluster

SUBMITTER: Yoshimura Y 

PROVIDER: S-EPMC9710696 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature