{"title":"用网络方法鉴定宫颈癌关键基因的转录组meta分析","authors":"P. Sadeghi, Amir Zarei, M. Sadeghi","doi":"10.29252/qums.13.10.53","DOIUrl":null,"url":null,"abstract":"Received: 28 Oct, 2018 Accepted: 11 Dec, 2019 Abstract Background and Objectives: Cervical cancer is one of the most prevalent cancers among women. Accurate diagnosis and treatment of complex diseases require precise identification of molecular characteristics of the disease. Transcriptome profiles provide valuable information on gene expression of the studied cells. Applying metaanalysis approache along with network-based approaches provides precise and valuable information about studied data, which can be used in developing new diagnostic and therapeutic methods. The aim of this study was meta-analysis investigation of cervical cancer transcriptome using a network approach in order to identify key genes in the disease.","PeriodicalId":20865,"journal":{"name":"Qom University of Medical Sciences Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Meta-Analysis of Cervical Cancer Transcriptome with a Network Approach to Identify Key Genes in the Disease\",\"authors\":\"P. Sadeghi, Amir Zarei, M. Sadeghi\",\"doi\":\"10.29252/qums.13.10.53\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Received: 28 Oct, 2018 Accepted: 11 Dec, 2019 Abstract Background and Objectives: Cervical cancer is one of the most prevalent cancers among women. Accurate diagnosis and treatment of complex diseases require precise identification of molecular characteristics of the disease. Transcriptome profiles provide valuable information on gene expression of the studied cells. Applying metaanalysis approache along with network-based approaches provides precise and valuable information about studied data, which can be used in developing new diagnostic and therapeutic methods. The aim of this study was meta-analysis investigation of cervical cancer transcriptome using a network approach in order to identify key genes in the disease.\",\"PeriodicalId\":20865,\"journal\":{\"name\":\"Qom University of Medical Sciences Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Qom University of Medical Sciences Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.29252/qums.13.10.53\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Qom University of Medical Sciences Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29252/qums.13.10.53","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Meta-Analysis of Cervical Cancer Transcriptome with a Network Approach to Identify Key Genes in the Disease
Received: 28 Oct, 2018 Accepted: 11 Dec, 2019 Abstract Background and Objectives: Cervical cancer is one of the most prevalent cancers among women. Accurate diagnosis and treatment of complex diseases require precise identification of molecular characteristics of the disease. Transcriptome profiles provide valuable information on gene expression of the studied cells. Applying metaanalysis approache along with network-based approaches provides precise and valuable information about studied data, which can be used in developing new diagnostic and therapeutic methods. The aim of this study was meta-analysis investigation of cervical cancer transcriptome using a network approach in order to identify key genes in the disease.
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