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High Performance Genomic Sequencing: A Filtered Approach

机译:高性能基因组测序:过滤方法

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摘要

Protein and DNA homology detection systems are an essential part in computational biology applications. These algorithms have changed over the time from dynamic programming approaches by finding the optimal local alignment between two sequences to statistical approaches with different kinds of heuristics that minimize former executions times. However, the continuously increasing size of input datasets is being projected into the use of High Performance Computing (HPC) hardware and software in order to address this problem. The aim of the research presented in this paper is to propose a new filtering methodology, based on general-purpose graphical processor units (GP-GPUs) and multi-core processors, for removing those sequences considered irrelevant in terms of homology and similarity. The proposed methodology is completely independent from the homology detection algorithm. This approach is very useful for researchers and practitioners because they do not need to understand a new algorithm. This design has been approved by the National Biotechnology Research Center of Spain (CNB).
机译:蛋白质和DNA同源性检测系统是计算生物学应用中的重要组成部分。这些算法已经发生了变化,从动态规划方法通过寻找两个序列之间的最佳局部比对与不同类型的启发式,最大限度地减少执行死刑前时代统计方法的时间。但是,输入数据集的连续增加尺寸正在投影到使用高性能计算(HPC)硬件和软件以解决此问题。本文提出的研究的目的是提出基于通用图形处理器单元(GP-GPU)和多核处理器的新过滤方法,以除去在同源性和相似性方面被认为无关的那些序列。所提出的方法完全独立于同源检测算法。这种方法对于研究人员和从业者来说非常有用,因为它们不需要了解一种新的算法。该设计已获得西班牙国家生物技术研究中心(CNB)批准。

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