Integrating Pre-Trained protein language model and multiple window scanning deep learning networks for accurate identification of secondary active transporters in membrane proteins-Reference-Cited by-同舟云学术

Integrating Pre-Trained protein language model and multiple window scanning deep learning networks for accurate identification of secondary active transporters in membrane proteins

Published:2023-12 Issue: Volume:220 Page:11-20
ISSN:1046-2023
Container-title:Methods
language:en
Short-container-title:Methods

Author:

Shahid Malik Muhammad,Ou Yu-Yen

Funder

National Science and Technology Council

Ministry of Science and Technology, Taiwan

Publisher

Elsevier BV

Subject

General Biochemistry, Genetics and Molecular Biology,Molecular Biology

Reference31 articles.

1. Classification systems of secondary active transporters;Perland;Trends Pharmacol. Sci.,2017

2. Targeting SLC transporters: small molecules as modulators and therapeutic opportunities;Schlessinger;Trends Biochem. Sci,2023

3. A structure and evolutionary-based classification of solute carriers;Ferrada;Iscience,2022

4. A guide to plasma membrane solute carrier proteins;Pizzagalli;FEBS J.,2021

5. Sodium-glucose cotransporters: new targets of cancer therapy?;Vrhovac Madunić;Arh. Hig. Rada Toksikol.,2018

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