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Elife|December 28, 2022
Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteriaMu Gao, Davi Nakajima An, Jeffrey SkolnickNature Communications|April 2, 2022
AF2Complex predicts direct physical interactions in multimeric proteins with deep learningMu Gao, Davi Nakajima An, Jerry M Parks, et al.Proceedings of the National Academy of Sciences of the United States of America|February 23, 2012
The distribution of ligand-binding pockets around protein-protein interfaces suggests a general mechanism for pocket formationMu Gao, Jeffrey SkolnickNucleic Acids Research|June 3, 2008
DBD-Hunter: a knowledge-based method for the prediction of DNA-protein interactionsMu Gao, Jeffrey SkolnickProteins|March 3, 2011
New benchmark metrics for protein-protein docking methodsMu Gao, Jeffrey SkolnickPlos Computational Biology|April 4, 2009
From nonspecific DNA-protein encounter complexes to the prediction of DNA-protein interactionsMu Gao, Jeffrey SkolnickBioinformatics (Oxford, England)|September 22, 2020
A novel sequence alignment algorithm based on deep learning of the protein folding codeMu Gao, Jeffrey SkolnickFrontiers in Bioinformatics|July 26, 2021
A General Framework to Learn Tertiary Structure for Protein Sequence CharacterizationMu Gao, Jeffrey SkolnickBioinformatics (Oxford, England)|January 22, 2013
APoc: large-scale identification of similar protein pocketsMu Gao, Jeffrey SkolnickProceedings of the National Academy of Sciences of the United States of America|December 15, 2010
Structural space of protein-protein interfaces is degenerate, close to complete, and highly connectedMu Gao, Jeffrey SkolnickPageof 21