{"title":"PROGmiR:使用公开数据识别多种癌症预后miRNA生物标志物的工具。","authors":"Chirayu Pankaj Goswami, Harikrishna Nakshatri","doi":"10.1186/2043-9113-2-23","DOIUrl":null,"url":null,"abstract":"<p><strong>Unlabelled: </strong></p><p><strong>Background: </strong>Identification of prognostic biomarkers is hallmark of cancer genomics. Since miRNAs regulate expression of multiple genes, they act as potent biomarkers in several cancers. Identification of miRNAs that are prognostically important has been done sporadically, but no resource is available till date that allows users to study prognostics of miRNAs of interest, utilizing the wealth of available data, in major cancer types.</p><p><strong>Description: </strong>In this paper, we present a web based tool that allows users to study prognostic properties of miRNAs in several cancer types, using publicly available data. We have compiled data from Gene Expression Omnibus (GEO), and recently developed \"The Cancer Genome Atlas (TCGA)\", to create this tool. The tool is called \"PROGmiR\" and it is available at http://www.compbio.iupui.edu/progmir. Currently, our tool can be used to study overall survival implications for approximately 1050 human miRNAs in 16 major cancer types.</p><p><strong>Conclusions: </strong>We believe this resource, as a hypothesis generation tool, will be helpful for researchers to link miRNA expression with cancer outcome and to design mechanistic studies. We studied performance of our tool using identified miRNA biomarkers from published studies. The prognostic plots created using our tool for specific miRNAs in specific cancer types corroborated with the findings in the studies.</p>","PeriodicalId":73663,"journal":{"name":"Journal of clinical bioinformatics","volume":" ","pages":"23"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/2043-9113-2-23","citationCount":"54","resultStr":"{\"title\":\"PROGmiR: a tool for identifying prognostic miRNA biomarkers in multiple cancers using publicly available data.\",\"authors\":\"Chirayu Pankaj Goswami, Harikrishna Nakshatri\",\"doi\":\"10.1186/2043-9113-2-23\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Unlabelled: </strong></p><p><strong>Background: </strong>Identification of prognostic biomarkers is hallmark of cancer genomics. Since miRNAs regulate expression of multiple genes, they act as potent biomarkers in several cancers. Identification of miRNAs that are prognostically important has been done sporadically, but no resource is available till date that allows users to study prognostics of miRNAs of interest, utilizing the wealth of available data, in major cancer types.</p><p><strong>Description: </strong>In this paper, we present a web based tool that allows users to study prognostic properties of miRNAs in several cancer types, using publicly available data. We have compiled data from Gene Expression Omnibus (GEO), and recently developed \\\"The Cancer Genome Atlas (TCGA)\\\", to create this tool. The tool is called \\\"PROGmiR\\\" and it is available at http://www.compbio.iupui.edu/progmir. Currently, our tool can be used to study overall survival implications for approximately 1050 human miRNAs in 16 major cancer types.</p><p><strong>Conclusions: </strong>We believe this resource, as a hypothesis generation tool, will be helpful for researchers to link miRNA expression with cancer outcome and to design mechanistic studies. We studied performance of our tool using identified miRNA biomarkers from published studies. The prognostic plots created using our tool for specific miRNAs in specific cancer types corroborated with the findings in the studies.</p>\",\"PeriodicalId\":73663,\"journal\":{\"name\":\"Journal of clinical bioinformatics\",\"volume\":\" \",\"pages\":\"23\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1186/2043-9113-2-23\",\"citationCount\":\"54\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of clinical bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/2043-9113-2-23\",\"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 clinical bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/2043-9113-2-23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PROGmiR: a tool for identifying prognostic miRNA biomarkers in multiple cancers using publicly available data.
Unlabelled:
Background: Identification of prognostic biomarkers is hallmark of cancer genomics. Since miRNAs regulate expression of multiple genes, they act as potent biomarkers in several cancers. Identification of miRNAs that are prognostically important has been done sporadically, but no resource is available till date that allows users to study prognostics of miRNAs of interest, utilizing the wealth of available data, in major cancer types.
Description: In this paper, we present a web based tool that allows users to study prognostic properties of miRNAs in several cancer types, using publicly available data. We have compiled data from Gene Expression Omnibus (GEO), and recently developed "The Cancer Genome Atlas (TCGA)", to create this tool. The tool is called "PROGmiR" and it is available at http://www.compbio.iupui.edu/progmir. Currently, our tool can be used to study overall survival implications for approximately 1050 human miRNAs in 16 major cancer types.
Conclusions: We believe this resource, as a hypothesis generation tool, will be helpful for researchers to link miRNA expression with cancer outcome and to design mechanistic studies. We studied performance of our tool using identified miRNA biomarkers from published studies. The prognostic plots created using our tool for specific miRNAs in specific cancer types corroborated with the findings in the studies.