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3D Deep Learning for Biological Function Prediction from Physical Fields., , , , , , , and . 3DV, page 928-937. IEEE, (2020)PconsD: ultra rapid, accurate model quality assessment for protein structure prediction., and . Bioinform., 29 (14): 1817-1818 (2013)Improved predictions by Pcons.net using multiple templates., , , and . Bioinform., 27 (3): 426-427 (2011)Improved Contact Predictions Using the Recognition of Protein Like Contact Patterns., , , and . PLoS Comput. Biol., (2014)Mabellini: a genome-wide database for understanding the structural proteome and evaluating prospective antimicrobial targets of the emerging pathogen Mycobacterium abscessus., , , , , and . Database J. Biol. Databases Curation, (2019)Genome3D: integrating a collaborative data pipeline to expand the depth and breadth of consensus protein structure annotation., , , , , , , , , and 7 other author(s). Nucleic Acids Res., 48 (Database-Issue): D314-D319 (2020)PconsFold: improved contact predictions improve protein models., , , , , and . Bioinform., 30 (17): 482-488 (2014)Early computational detection of potential high-risk SARS-CoV-2 variants., , , , , , , , , and 5 other author(s). Comput. Biol. Medicine, (March 2023)Predicting accurate contacts in thousands of Pfam domain families using PconsC3., , , , and . Bioinform., 33 (18): 2859-2866 (2017)PconsC: combination of direct information methods and alignments improves contact prediction., , and . Bioinform., 29 (14): 1815-1816 (2013)