Pieter Moris, Danh Bui Thi, K. Laukens, P. Meysman
{"title":"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","authors":"Pieter Moris, Danh Bui Thi, K. Laukens, P. Meysman","doi":"10.1093/bioinformatics/btz849","DOIUrl":null,"url":null,"abstract":"\n \n \n 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.\n \n \n \n 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.\n \n \n \n Supplementary data are available at Bioinformatics online.\n","PeriodicalId":90576,"journal":{"name":"Journal of bioinformatics","volume":"252 1","pages":"1978-1980"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MILES: a Java tool to extract node-specific enriched subgraphs in biomolecular networks\",\"authors\":\"Pieter Moris, Danh Bui Thi, K. Laukens, P. Meysman\",\"doi\":\"10.1093/bioinformatics/btz849\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n \\n 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.\\n \\n \\n \\n 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.\\n \\n \\n \\n Supplementary data are available at Bioinformatics online.\\n\",\"PeriodicalId\":90576,\"journal\":{\"name\":\"Journal of bioinformatics\",\"volume\":\"252 1\",\"pages\":\"1978-1980\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/bioinformatics/btz849\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioinformatics/btz849","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.