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双团:用于二分图中最大双团枚举的R语言包。

Biclique: an R package for maximal biclique enumeration in bipartite graphs.

作者信息

Lu Yuping, Phillips Charles A, Langston Michael A

机构信息

Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.

Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, 37996-2250, USA.

出版信息

BMC Res Notes. 2020 Feb 21;13(1):88. doi: 10.1186/s13104-020-04955-0.

Abstract

OBJECTIVE

Bipartite graphs are widely used to model relationships between pairs of heterogeneous data types. Maximal bicliques are foundational structures in such graphs, and their enumeration is an important task in systems biology, epidemiology and many other problem domains. Thus, there is a need for an efficient, general purpose, publicly available tool to enumerate maximal bicliques in bipartite graphs. The statistical programming language R is a logical choice for such a tool, but until now no R package has existed for this purpose. Our objective is to provide such a package, so that the research community can more easily perform this computationally demanding task.

RESULTS

Biclique is an R package that takes as input a bipartite graph and produces a listing of all maximal bicliques in this graph. Input and output formats are straightforward, with examples provided both in this paper and in the package documentation. Biclique employs a state-of-the-art algorithm previously developed for basic research in functional genomics. This package, along with its source code and reference manual, are freely available from the CRAN public repository at https://cran.r-project.org/web/packages/biclique/index.html.

摘要

目标

二分图被广泛用于对异构数据类型对之间的关系进行建模。最大双团是此类图中的基础结构,对其进行枚举是系统生物学、流行病学及许多其他问题领域中的一项重要任务。因此,需要一个高效、通用且公开可用的工具来枚举二分图中的最大双团。统计编程语言R是实现此类工具的合理选择,但迄今为止尚未有用于此目的的R包。我们的目标是提供这样一个包,以便研究界能够更轻松地执行这项计算要求较高的任务。

结果

双团(Biclique)是一个R包,它将二分图作为输入,并生成该图中所有最大双团的列表。输入和输出格式很简单,本文及包文档中均提供了示例。双团采用了先前为功能基因组学基础研究而开发的先进算法。该包及其源代码和参考手册可从CRAN公共存储库(https://cran.r-project.org/web/packages/biclique/index.html)免费获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8eb5/7035696/013fcee11395/13104_2020_4955_Fig1_HTML.jpg

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