A Comparative Study of Sequence Clustering Algorithms

Zhen Ju

doi:10.26599/BDMA.2025.9020010

2025-10-01

PRE

DOI：10.26599/BDMA.2025.9020010

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摘要

En 中文

序列聚类软件在生物信息学中至关重要。然而，由于算法和应用场景的多样性，选择合适的软件可能具有挑战性。本文从精度、敏感性、速度、运行时间规模和内存消耗五个方面，分析和评估了八种代表性软件（算法）。此外，本文还考察了序列数量、序列长度、序列相似度、线程数和GPU对上述指标的影响。序列长度和序列相似度显著影响聚类效率（速度和内存消耗），其波动幅度超过一个数量级，并观察到非单调效应。评估结果被分析和总结在表格中供用户参考。

Keyword:

Performance evaluation

Sensitivity

Systematics

Instruction sets

Scalability

Software algorithms

Memory management

Clustering algorithms

Software

Protein sequence

protein sequence clustering

performance evaluation

gene sequence clustering

scalability

期刊

Big Data Mining and Analytics

IF:

6.2

论文数:

274

被引数:

1.0K

机构

university of chinese academy of sciences, cas

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4.1W

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被引数: 75

Chinese Academy of Sciences

学者数:

3.9W

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被引数: 58.4W

South China Agricultural University

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3.1W

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被引数: 2.6W

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