Predicting the multi-label protein subcellular localization through multi-information fusion and MLSI dimensionality reduction based on MLFE classifier.

ABSTRACT: Multi-label 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 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 COVID-19. The paper proposes a novel method named ML-locMLFE. First of all, six feature extraction methods are adopted to obtain protein effective information. These methods include pseudo amino acid composition (PseAAC), encoding based on grouped weight (EBGW), gene ontology (GO), multi-scale continuous and discontinuous (MCD), residue probing transformation (RPT) and evolutionary distance transformation (EDT). In the next part, we utilize the m

SUBMITTER: Liu Y 

PROVIDER: S-EPMC8690230 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature