F. Al-Shahrour, Javier Herrero, Á. Mateos, J. Santoyo, R. Díaz-Uriarte, J. Dopazo
{"title":"在基因组规模的研究中使用基因本体来发现与基因组相关的生物学术语的显著关联","authors":"F. Al-Shahrour, Javier Herrero, Á. Mateos, J. Santoyo, R. Díaz-Uriarte, J. Dopazo","doi":"10.1109/NNSP.2003.1318003","DOIUrl":null,"url":null,"abstract":"The analysis of genome-scale data from different high throughput techniques usually involves the grouping of genes based on experimental criteria. These groups are a consequence of the biological roles the genes are playing within the cell. Establishing which of these groups are functionally important is essential. Gene ontology terms provide a specialised vocabulary to describe the relevant biological properties of genes. We used a simple procedure to extract terms that are significantly over or under-represented in sets of genes within the context of a genome-scale experiment. Said procedure, which takes the multiple-testing nature of the statistical contrast into account, has been implemented as a Web application, FatiGO, allowing for easy and interactive querying. Several examples demonstrate its application and the type of information that can be extracted. Although a number of genes still lack gene ontology annotations, the results were informative enough to characterise the biological processes in the systems analysed.","PeriodicalId":315958,"journal":{"name":"2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718)","volume":"235 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Using gene ontology on genome-scale studies to find significant associations of biologically relevant terms to groups of genes\",\"authors\":\"F. Al-Shahrour, Javier Herrero, Á. Mateos, J. Santoyo, R. Díaz-Uriarte, J. Dopazo\",\"doi\":\"10.1109/NNSP.2003.1318003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The analysis of genome-scale data from different high throughput techniques usually involves the grouping of genes based on experimental criteria. These groups are a consequence of the biological roles the genes are playing within the cell. Establishing which of these groups are functionally important is essential. Gene ontology terms provide a specialised vocabulary to describe the relevant biological properties of genes. We used a simple procedure to extract terms that are significantly over or under-represented in sets of genes within the context of a genome-scale experiment. Said procedure, which takes the multiple-testing nature of the statistical contrast into account, has been implemented as a Web application, FatiGO, allowing for easy and interactive querying. Several examples demonstrate its application and the type of information that can be extracted. Although a number of genes still lack gene ontology annotations, the results were informative enough to characterise the biological processes in the systems analysed.\",\"PeriodicalId\":315958,\"journal\":{\"name\":\"2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718)\",\"volume\":\"235 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NNSP.2003.1318003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NNSP.2003.1318003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using gene ontology on genome-scale studies to find significant associations of biologically relevant terms to groups of genes
The analysis of genome-scale data from different high throughput techniques usually involves the grouping of genes based on experimental criteria. These groups are a consequence of the biological roles the genes are playing within the cell. Establishing which of these groups are functionally important is essential. Gene ontology terms provide a specialised vocabulary to describe the relevant biological properties of genes. We used a simple procedure to extract terms that are significantly over or under-represented in sets of genes within the context of a genome-scale experiment. Said procedure, which takes the multiple-testing nature of the statistical contrast into account, has been implemented as a Web application, FatiGO, allowing for easy and interactive querying. Several examples demonstrate its application and the type of information that can be extracted. Although a number of genes still lack gene ontology annotations, the results were informative enough to characterise the biological processes in the systems analysed.