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A systematic exploration of ΔΔG cutoff ranges in machine learning models for protein mutation stability prediction.

, , , and . J. Bioinform. Comput. Biol., 16 (5): 1840022:1-1840022:19 (2018)

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CONSEQUENCES: CONstrained SEQUENCE alignmentS With Multiple User Weights., , , , , and . BCB, page 574-579. ACM, (2019)Using Rigidity Analysis to Probe Mutation-induced Structural Changes in proteins., , and . J. Bioinform. Comput. Biol., (2012)Towards sequence-based DNA flexibility analysis., , and . BCB, page 607-609. ACM, (2012)Big Holes in Big Data: A Monte Carlo Algorithm for Detecting Large Hyper-Rectangles in High Dimensional Data., , and . COMPSAC, page 563-571. IEEE Computer Society, (2016)CGRAP: A Web Server for Coarse-Grained Rigidity Analysis of Proteins., , , , , and . Symmetry, 13 (12): 2401 (2021)Assessing the Effects of Amino Acid Insertion and Deletion Mutations., , , and . BIBM, page 2511-2518. IEEE, (2021)KINARI-Web: a server for protein rigidity analysis., , , and . Nucleic Acids Res., 39 (Web-Server-Issue): 177-183 (2011)An extensible software infrastructure for testing the evolutionary consequences of developmental interactions., , and . BCB, page 557-558. ACM, (2015)Towards biophysical validation of constraint modeling for rigidity analysis of proteins., and . BCB, page 408-413. ACM, (2012)Big Holes in Big Data: A Monte Carlo Algorithm for Detecting Large Hyper-rectangles in High Dimensional Data., , and . CoRR, (2017)