{"title":"ACM-BCB '17教程:机器人启发算法建模蛋白质结构和运动","authors":"Kevin Molloy, David Morris, Amarda Shehu","doi":"10.1145/3107411.3107493","DOIUrl":null,"url":null,"abstract":"With biomolecular structure recognized as central to understanding mechanisms in the cell, computational chemists and biophysicists have spent significant efforts on modeling structure and dynamics. While significant advances have been made, particularly in the design of sophisticated energetic models and molecular representations, such efforts are experiencing diminishing returns. One of the culprits is low exploration capability. The impasse has attracted AI researchers to offer adaptations of robot motion planning algorithms for modeling biomolecular structures and motions. This tutorial introduces students and researchers to robotics-inspired treatments and methodologies for understanding and elucidating the role of structure and dynamics in the function of biomolecules. The presentation is enhanced via an open-source software developed in the Shehu Computational Biology laboratory. The software allows researchers to integrate themselves in a new research domain and drive further research via plug-and-play capabilities. The hands-on approach in the the tutorial benefits both students and senior researchers keen to make contributions in computational structural biology.","PeriodicalId":246388,"journal":{"name":"Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ACM-BCB '17 Tutorial: Robotics-inspired Algorithms for Modeling Protein Structures and Motions\",\"authors\":\"Kevin Molloy, David Morris, Amarda Shehu\",\"doi\":\"10.1145/3107411.3107493\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With biomolecular structure recognized as central to understanding mechanisms in the cell, computational chemists and biophysicists have spent significant efforts on modeling structure and dynamics. While significant advances have been made, particularly in the design of sophisticated energetic models and molecular representations, such efforts are experiencing diminishing returns. One of the culprits is low exploration capability. The impasse has attracted AI researchers to offer adaptations of robot motion planning algorithms for modeling biomolecular structures and motions. This tutorial introduces students and researchers to robotics-inspired treatments and methodologies for understanding and elucidating the role of structure and dynamics in the function of biomolecules. The presentation is enhanced via an open-source software developed in the Shehu Computational Biology laboratory. The software allows researchers to integrate themselves in a new research domain and drive further research via plug-and-play capabilities. The hands-on approach in the the tutorial benefits both students and senior researchers keen to make contributions in computational structural biology.\",\"PeriodicalId\":246388,\"journal\":{\"name\":\"Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3107411.3107493\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3107411.3107493","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ACM-BCB '17 Tutorial: Robotics-inspired Algorithms for Modeling Protein Structures and Motions
With biomolecular structure recognized as central to understanding mechanisms in the cell, computational chemists and biophysicists have spent significant efforts on modeling structure and dynamics. While significant advances have been made, particularly in the design of sophisticated energetic models and molecular representations, such efforts are experiencing diminishing returns. One of the culprits is low exploration capability. The impasse has attracted AI researchers to offer adaptations of robot motion planning algorithms for modeling biomolecular structures and motions. This tutorial introduces students and researchers to robotics-inspired treatments and methodologies for understanding and elucidating the role of structure and dynamics in the function of biomolecules. The presentation is enhanced via an open-source software developed in the Shehu Computational Biology laboratory. The software allows researchers to integrate themselves in a new research domain and drive further research via plug-and-play capabilities. The hands-on approach in the the tutorial benefits both students and senior researchers keen to make contributions in computational structural biology.