Work

I-TASSER-MTD: a deep-learning-based platform for multi-domain protein structure and function prediction

Year: 2022

Type: article

Source: Nature Protocols

DOI: 10.1038/s41596-022-00728-0

Authors: Xiaogen Zhou, Wei Zheng, Yang Li, Robin Pearce, Chengxin Zhang, Eric W. Bell, Guijun Zhang, Yang Zhang

Institutions: University of Michigan, Zhejiang University of Technology

Language: English

Topic: Protein Structure and Dynamics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: closed

Funders: National Science Foundation, U.S. Department of Health and Human Services, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Natural Science Foundation of China, National Institutes of Health, National Natural Science Foundation of China-Yunnan Joint Fund, National Institute of General Medical Sciences

Awards: IIBR: Informatics: RAPID: Genome-wide Structure and Function Modeling of the SARS-CoV-2 Virus, G1522358159, G2284547183, G2464480468, G2708836668, Advanced approaches to protein structure prediction, G3624401757, G3775454306, G5858409502, G7897283973, High-Performance Computing Cluster for Biomedical Research, G8786657440

OpenAlex ID: W4295165394

FWCI: 33.02

Cites: 112

Cited by: 538

Related to: 10