Identification of Genome Sequences of Polyphosphate-Accumulating Organisms by Machine Learning.

ABSTRACT: In the field of sewage treatment, the identification of polyphosphate-accumulating organisms (PAOs) usually relies on biological experiments. However, biological experiments are not only complicated and time-consuming, but also costly. In recent years, machine learning has been widely used in many fields, but it is seldom used in the water treatment. The present work presented a high accuracy support vector machine (SVM) algorithm to realize the rapid identification and prediction of PAOs. We obtained 6,318 genome sequences of microorganisms from the publicly available microbial genome database for comparative analysis (MBGD). Minimap2 was used to compare the genomes of the obtained microorganisms in pairs, and read the overlap. The SVM model was established using the similarity of the gen

SUBMITTER: Liu B 

PROVIDER: S-EPMC7848102 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature