Open AccessPredicting the multi-label protein subcellular localization through multi-information fusion and MLSI dimensionality reduction based on MLFE classifier
Author(s) -
Yushuang Liu,
Shuping Jin,
Hongli Gao,
Xue Wang,
Congjing Wang,
Weifeng Zhou,
Bin Yu
Publication year - 2021
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btab811
Subject(s) - pseudo amino acid composition , computer science , artificial intelligence , classifier (uml) , pattern recognition (psychology) , dimensionality reduction , machine learning , data mining , computational biology , subcellular localization , gene , biology , biochemistry
Multi-label (ML) protein subcellular localization (SCL) is an indispensable way to study protein function. It can locate a certain protein (such as the human transmembrane protein that promotes the invasion of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)) or expression product at a specific location in a cell, which can provide a reference for clinical treatment of diseases such as coronavirus disease 2019 (COVID-19).