Prediction of lysine formylation sites using support vector machine based on the sample selection from majority classes and synthetic minority over-sampling techniques-Reference-Cited by-同舟云学术

Prediction of lysine formylation sites using support vector machine based on the sample selection from majority classes and synthetic minority over-sampling techniques

Published:2022-01 Issue: Volume:192 Page:125-135
ISSN:0300-9084
Container-title:Biochimie
language:en
Short-container-title:Biochimie

Author:

Sohrawordi Md.,Hossain Md. Ali

Publisher

Elsevier BV

Subject

General Medicine,Biochemistry

Reference69 articles.

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4. dForml(KNN)-PseAAC: Detecting formylation sites from protein sequences using K-nearest neighbor algorithm via Chou's 5-step rule and pseudo components;Ning;J. Theor. Biol.,2019

5. Prediction of lysine formylation sites using the composition of k-spaced amino acid pairs via Chou's 5-steps rule and general pseudo components;Ju;Genomics,2020

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