MILES:一个Java工具,用于提取生物分子网络中特定节点的富集子图

Pieter Moris, Danh Bui Thi, K. Laukens, P. Meysman
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引用次数: 0

摘要

生物分子网络的日益可用性导致了对能够从这些复杂的数据结构中提取生物学上有意义的信息的分析方法的需求。在这里,我们提出了MILES (MIning Labeled enrichment Subgraphs),这是一种基于java的子图挖掘工具,用于发现生物分子网络中与一组给定感兴趣的节点(如基因或蛋白质列表)相关的基元。它为广泛使用的富集分析方法提供了一个独特的扩展,通过集成网络结构和功能注释来识别新的生物子图,这些子图富含感兴趣的目标。该工具可以处理各种类型的输入数据,包括(非)定向、(非)连接和多标签网络,因此与大多数类型的生物分子网络兼容。MILES是一个独立于平台的Java应用程序,可在https://github.com/pmoris/miles-subgraph-miner上获得,附带用户手册、示例数据集和源代码。补充数据可在生物信息学网站获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MILES: a Java tool to extract node-specific enriched subgraphs in biomolecular networks
The growing availability of biomolecular networks has led to a need for analysis methods that are able to extract biologically meaningful information from these complex data structures. Here we present MILES (MIning Labeled Enriched Subgraphs), a Java-based subgraph mining tool for discovering motifs that are associated to a given set of nodes of interest, such as a list of genes or proteins, in biomolecular networks. It provides a unique extension to the widely used enrichment analysis methodologies by integrating network structure and functional annotations in order to discern novel biological subgraphs which are enriched in the targets of interest. The tool can handle various types of input data, including (un)directed, (un)connected and multi-label networks, and is thus compatible with most types of biomolecular networks. MILES is available as a platform-independent Java application at https://github.com/pmoris/miles-subgraph-miner alongside a user manual, example datasets and the source code. Supplementary data are available at Bioinformatics online.
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