UPFPSR: a ubiquitylation predictor for plant through combining sequence information and random forest

DOI10.3934/mbe.2022035zbMath1489.92112OpenAlexW4200220484MaRDI QIDQ2130126

Cangzhi Jia, Shuwan Yin, Quan Zou, Zhengkui Lin, Hua Shi, Jia Zheng

Publication date: 25 April 2022

Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)

Full work available at URL: https://doaj.org/article/2c51fd0518264d959563d0e41e4026d7

zbMATH Keywords

deep learninglysine ubiquitylationprotein post-translational modificationstest evaluationtraditional machine learning

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Protein sequences, DNA sequences (92D20) Plant biology (92C80)

Related Items (1)

UPFPSR

Uses Software

• PseAAC
• GitHub
• iFeature
• hCKSAAP_UbSite
• DeepVF

Cites Work

• pSuc-Lys: predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach
• Dforml(KNN)-PseAAC: detecting formylation sites from protein sequences using K-nearest neighbor algorithm via Chou's 5-step rule and pseudo components
• Random forests

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