Extensive comparison of protein sequence-based bioinformatics applications for predicting lysine succinylation sites: a comparative review DOI Creative Commons
Hussam Alsharif

Biotechnology & Biotechnological Equipment, Год журнала: 2024, Номер 38(1)

Опубликована: Ноя. 12, 2024

Lysine succinylation is a post-translational modification that occurs when succinyl group bonds with lysine residue and changes the polarity of from positive to negative, causing significant in structure functioning proteins. on various proteins crucial cellular biological processes eukaryotic prokaryotic organisms. Succinylation site identification an area high research interest, sequence-based prediction methods using machine learning deep have been developed based experimentally confirmed data sites, aiming be highly accurate, robust, quick, cost-efficient. However, despite usefulness these methods, different issues must addressed building model succinylation. As predictors become more abundant, it assess their advantages drawbacks identify potential improve efficiency predicting sites. Among multiple studies employed machine-learning deep-learning applications, few systematically examined computational issues. Hence, this review, we summarize challenges restrictions development models provide guidelines for suitable efficient methods.

Язык: Английский

NEAT1 Promotes the Perineural Invasion of Pancreatic Cancer via the E2F1/GDNF Axis DOI
Jingtao Gu, Qiqi Wang,

Jiantao Mo

и другие.

Cancer Letters, Год журнала: 2025, Номер unknown, С. 217497 - 217497

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Extensive comparison of protein sequence-based bioinformatics applications for predicting lysine succinylation sites: a comparative review DOI Creative Commons
Hussam Alsharif

Biotechnology & Biotechnological Equipment, Год журнала: 2024, Номер 38(1)

Опубликована: Ноя. 12, 2024

Lysine succinylation is a post-translational modification that occurs when succinyl group bonds with lysine residue and changes the polarity of from positive to negative, causing significant in structure functioning proteins. on various proteins crucial cellular biological processes eukaryotic prokaryotic organisms. Succinylation site identification an area high research interest, sequence-based prediction methods using machine learning deep have been developed based experimentally confirmed data sites, aiming be highly accurate, robust, quick, cost-efficient. However, despite usefulness these methods, different issues must addressed building model succinylation. As predictors become more abundant, it assess their advantages drawbacks identify potential improve efficiency predicting sites. Among multiple studies employed machine-learning deep-learning applications, few systematically examined computational issues. Hence, this review, we summarize challenges restrictions development models provide guidelines for suitable efficient methods.

Язык: Английский

Процитировано

0