ArticleBioinformatics advances2021
Genomic style: yet another deep-learning approach to characterize bacterial genome sequences.
Article in Bioinformatics advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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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 Results: We propose a novel sequence feature, called genomic style, inspired by image classification approaches, for classifying and clustering DNA sequences. As with the style of images, the DNA sequence is considered to have a genomic style unique to the bacterial species, and the style matrix concept is applied to the DNA sequence. Our main aim is to introduce the genomics style as yet another basic sequence feature for metagenome binning problem in replace of the most commonly used sequence feature Availability and implementation: The source code for the implementation of this genomic style method, along with the dataset for the performance evaluation, is available from https://github.com/friendflower94/binning-style. Supplementary information: Supplementary data are available at
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