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Parallel Decomposition of 3D Surfaces in Images of Local Descriptors for Molecular Screening

机译:用于分子筛选的局部描述符图像中3D表面的平行分解

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An emerging application field for structure matching is related to in silico studies of molecular biology. Considering that protein function is mainly related to its external morphology, the possibility to match macromolecular surfaces is very important to infer information about the possible interaction and function of biological components. Most of the present approaches aim to match complete objects and they exploit a complete 3D representations of them. These aspects do not suit well with the local formulation of the matching issue in the biological application domain. The problem is that the shapes of macromolecules that are experimentally known to dock cannot present high similarities except in small important functional regions. This is the reason why we chose to adapt a well known image based method, originally studied for matching similar structures, for screening possible interactions of couples of macromolecule. In this context the proposed work presents a parallel algorithm able to efficiently decompose high detailed 3D surfaces into a proper set of images to use for the macromolecular screening.
机译:结构匹配的新兴应用领域与分子生物学的计算机研究有关。考虑到蛋白质功能主要与其外部形态有关,匹配大分子表面的可能性对于推断有关生物成分可能相互作用和功能的信息非常重要。当前的大多数方法旨在匹配完整的对象,并且它们利用了它们的完整3D表示。这些方面与生物应用领域中匹配问题的局部表达不太吻合。问题在于,除了在重要的小功能区域外,实验上已知可对接的大分子的形状无法表现出很高的相似性。这就是为什么我们选择采用一种众所周知的基于图像的方法的原因,该方法最初是为匹配相似的结构而研究的,用于筛选大分子对可能发生的相互作用。在这种情况下,提出的工作提出了一种并行算法,该算法能够有效地将高细节的3D表面分解为一组适当的图像,以用于大分子筛选。

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