K-mer计数:内存效率策略、并行计算及其在生物信息学中的应用领域

2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Pub Date : 2018-12-01 DOI:10.1109/BIBM.2018.8621325

Ming Xiao, Jiakun Li, Song Hong, Yongtao Yang, Junhua Li, Jian-xin Wang, Jian Yang, W. Ding, Le Zhang

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引用次数: 4

摘要

k-mer计数是目前生物信息学研究的一种重要算法。本文首先综述了k-mer计数在生物信息学中的主要应用领域。接下来，我们将介绍k-mer计数工具常用的内存效率策略，因为大量的内存请求是k-mer计数工具的瓶颈。接下来，我们阐述了当前k-mer计数工具的并行计算技术。最后，对k-mer计数的未来研究进行了展望。

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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K-mer Counting: memory-efficient strategy, parallel computing and field of application for Bioinformatics

Currently, k-mer counting is an important algorithm for bioinformatics research. This review lists the major application fields of k-mer counting in Bioinformatics at the beginning. Next, we introduce the commonly used memory-efficient strategy for k-mer counting tools, because the large amount of memory request is a bottleneck of k-mer counting tools. Next we illustrate the current parallel computing technologies for k-mer counting tool. Finally, we discuss the future study for k-mer counting.

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2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

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