PSBP-SVM: A Machine Learning-Based Computational Identifier for Predicting Polystyrene Binding Peptides

PSBP-SVM: A Machine Learning-Based Computational Identifier for Predicting Polystyrene Binding Peptides

Polystyrene binding peptides (PSBPs) play a key role in the immobilization process. The correct identification of PSBPs is the first step of all related works. In this paper, we proposed a novel support vector machine-based bioinformatic identification model. This model contains four machine learnin...

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Bibliographic Details
Main Authors: Chaolu Meng, Yang Hu, Ying Zhang, Fei Guo
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-03-01
Series:Frontiers in Bioengineering and Biotechnology
Subjects:
polystyrene binding peptides
support vector machine
bioinformatic
machine learning
identifier
Online Access:https://www.frontiersin.org/article/10.3389/fbioe.2020.00245/full

Internet

https://www.frontiersin.org/article/10.3389/fbioe.2020.00245/full

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