Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations is a research paper published in Cell Reports Methods (2021). On theSindex it has a DataRank of 0.958. It has been cited 593 times.
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Base Score Contribution
0.958
From this paper's citation signal
Citation Network Contribution
0
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This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
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Grant: R35 GM136422
National Science Foundation
Grant: ACI1548562
National Science Foundation
Grant: MTM2025426
NIGMS NIH HHS
Grant: R01 GM083107
National Institute of Allergy and Infectious Diseases
Grant: AI134678
NCI NIH HHS
Grant: T32 CA140044
NSF IIS
Grant: IIS1901191
NIGMS NIH HHS
Grant: T32 GM070449
NSF DBI
Grant: DBI2030790
National Institute of General Medical Sciences
Grant: GM136422
NIH HHS
Grant: S10 OD026825
NIAID NIH HHS
Grant: R01 AI134678
National Institutes of Health
Grant: 5R35GM136422-02
Advanced approaches to protein structure prediction
National Institutes of Health
Grant: 1S10OD026825-01A1
High-Performance Computing Cluster for Biomedical Research
National Science Foundation
Grant: 1901191
III: Medium: Collaborative Research: Multi-level computational approaches to protein function prediction
National Science Foundation
Grant: 2025426
MTM 2: Combining structural informatics and crosslinking mass spectrometry to predict the key protein-protein interactions shaping symbiotic microbial communities
National Science Foundation
Grant: 2030790
IIBR: Informatics: RAPID: Genome-wide Structure and Function Modeling of the SARS-CoV-2 Virus
National Institutes of Health
Grant: 5R01AI134678-03
Structure-based functional annotation of microbial genomes
NSF
FWCI
33.78
Citation Percentile
1.0%
Citation Trend
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