ACM-BCB '17 Tutorial: Robotics-inspired Algorithms for Modeling Protein Structures and Motions

Kevin Molloy, David Morris, Amarda Shehu
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引用次数: 0

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.
ACM-BCB '17教程:机器人启发算法建模蛋白质结构和运动
随着生物分子结构被认为是理解细胞机制的核心,计算化学家和生物物理学家在结构和动力学建模上付出了巨大的努力。虽然已经取得了重大进展,特别是在复杂的能量模型和分子表征的设计方面,但这些努力正在经历收益递减的过程。其中一个原因是勘探能力低。这一僵局吸引了人工智能研究人员提供机器人运动规划算法的适应性,以模拟生物分子结构和运动。本教程向学生和研究人员介绍机器人启发的治疗和方法,以理解和阐明生物分子功能中结构和动力学的作用。该演示通过Shehu计算生物学实验室开发的开源软件进行增强。该软件允许研究人员将自己整合到一个新的研究领域,并通过即插即用功能推动进一步的研究。本教程中的动手方法对学生和渴望在计算结构生物学方面做出贡献的高级研究人员都有好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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