predML-Site: Predicting Multiple Lysine PTM Sites With Optimal Feature Representation and Data Imbalance Minimization

Sabit Ahmed; Afrida Rahman; Md. Al Mehedi HasanJulia RahmanMd Khaled Ben IslamShamim Ahmad

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predML-Site: Predicting Multiple Lysine PTM Sites With Optimal Feature Representation and Data Imbalance Minimization

机译：predML-Site: Predicting Multiple Lysine PTM Sites With Optimal Feature Representation and Data Imbalance Minimization

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Identifying of post-translational modifications (PTM) is crucial in the study of computational proteomics, cell biology, pathogenesis, and drug development due to its role in many bio-molecular mechanisms. Computational methods for predicting multiple PTM at the same lysine residues, often referred to as K-PTM, is still evolving. This paper presents a novel computational tool, abbreviated as predML-Site, for predicting KPTM, such as acetylation, crotonylation, methylation, succinylation from an uncategorized peptide sample involving single, multiple, or no modification. For informative feature representation, multiple sequence encoding schemes, such as the sequence-coupling, binary encoding, k-spaced amino acid pairs, amino acid factor have been used with ANOVA and incremental feature selection. As a core predictor, a cost-sensitive SVM classifier has been adopted which effectively mitigates the effect of class-label imbalance in the dataset. predML-Site predicts multi-label PTM sites with 84.18% accuracy using the top 91 features. It has also achieved 85.34% aiming and 86.58% coverage rate which are much better than the existing state-of-the-art predictors on the same rigorous validation test. This performance indicates that predML-Site can be used as a supportive tool for further K-PTM study. For the convenience of the experimental scientists, predML-Site has been deployed as a user-friendly web-server at http://103.99.176.239/predML-Site .

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《IEEE/ACM transactions on computational biology and bioinformatics》 |2022年第6期|3624-3634|共11页
作者
Sabit Ahmed; Afrida Rahman; Md. Al Mehedi HasanJulia RahmanMd Khaled Ben IslamShamim Ahmad;
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作者单位

Department of Computer Science and Engineering, University of Rajshahi, Rajshahi, Bangladesh;

Department of Computer Science and Engineering, Rajshahi University of Engineering and Technology, Kazla, Rajshahi, Bangladesh;

Institute for Integrated and Intelligent Systems, Griffith University, Brisbane, QLD, AustraliaDepartment of Computer Science and Engineering, Pabna University of Science and Technology, Pabna, Bangladesh;

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原文格式 PDF
正文语种英语
中图分类生物信息论;
关键词
Amino acids; Peptides; Encoding; Proteins; Feature extraction; Benchmark testing; Tools;

predML-Site: Predicting Multiple Lysine PTM Sites With Optimal Feature Representation and Data Imbalance Minimization

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