Hybrid framework for membrane protein type prediction based on the PSSM-Reference-Cited by-同舟云学术

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Hybrid framework for membrane protein type prediction based on the PSSM

Published:2024-07-26 Issue:1 Volume:14 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Ruan Xiaoli,Xia Sina,Li Shaobo,Su Zhidong,Yang Jing

Funder

Guizhou Provincial Basic Research Program (Natural Science) Grant

Guizhou University Talents Project Grant

National Natural Science Foundation of China under Grant

Developing Objects and Projects of Scientific and Technological Talents in Guiyang City Grant

Publisher

Springer Science and Business Media LLC

Link

https://www.nature.com/articles/s41598-024-68163-7.pdf

Reference35 articles.

1. Levental, I. & Lyman, E. Regulation of membrane protein structure and function by their lipid nano-environment. Nat. Rev. Mol. Cell Biol. 24(2), 107–122 (2023).

2. Zhang, X. & Chen, L. Prediction of membrane protein types by fusing protein-protein interaction and protein sequence information. Biochim. Biophys. Acta (BBA)-Proteins Proteomics 1868(12), 140524 (2020).

3. Gulsevin, A. et al. Template-free prediction of a new monotopic membrane protein fold and oligomeric assembly by Alphafold2. Biophys. J . 122(3), 194a (2023).

4. Sankari, E. S. & Manimegalai, D. Predicting membrane protein types using various decision tree classifiers based on various modes of general PseAAC for imbalanced datasets. J. Theor. Biol. 435, 208–217 (2017).

5. Li, Z. et al. Predicting membrane protein contacts from non-membrane proteins by deep transfer learning. (2017). Preprint at http://arxiv.org/abs/1704.07207.

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