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Nucleic Acids Research|May 24, 2022
CSM-Potential: mapping protein interactions and biological ligands in 3D space using geometric deep learningCarlos H M Rodrigues, David B AscherProteins|October 23, 2023
CSM-Potential2: A comprehensive deep learning platform for the analysis of protein interacting interfacesCarlos H M Rodrigues, David B AscherHuman Genetics|January 16, 2024
Exploring the effects of missense mutations on protein thermodynamics through structure-based approaches: findings from the CAGI6 challengesCarlos H M Rodrigues, Stephanie Portelli, David B AscherPharmaceutics|February 25, 2023
CSM-Toxin: A Web-Server for Predicting Protein ToxicityVladimir Morozov, Carlos H M Rodrigues, David B AscherNucleic Acids Research|May 30, 2020
mCSM-membrane: predicting the effects of mutations on transmembrane proteinsDouglas E V Pires, Carlos H M Rodrigues, David B AscherNucleic Acids Research|April 24, 2021
mmCSM-PPI: predicting the effects of multiple point mutations on protein-protein interactionsCarlos H M Rodrigues, Douglas E V Pires, David B AscherProtein Science : a Publication of the Protein Society|July 9, 2024
EFG-CS: Predicting chemical shifts from amino acid sequences with protein structure prediction using machine learning and deep learning modelsXiaotong Gu, Yoochan Myung, Carlos H M Rodrigues, et al.Protein Science : a Publication of the Protein Society|September 4, 2020
DynaMut2: Assessing changes in stability and flexibility upon single and multiple point missense mutationsCarlos H M Rodrigues, Douglas E V Pires, David B AscherNucleic Acids Research|May 23, 2024
DDMut-PPI: predicting effects of mutations on protein-protein interactions using graph-based deep learningYunzhuo Zhou, YooChan Myung, Carlos H M Rodrigues, et al.Journal of Chemical Information and Modeling|November 1, 2021
pdCSM-PPI: Using Graph-Based Signatures to Identify Protein-Protein Interaction InhibitorsCarlos H M Rodrigues, Douglas E V Pires, David B AscherPageof 20