Weighted Gene Co-expression Network Analysis in Identification of Endometrial Cancer Prognosis Markers
نویسندگان
چکیده
منابع مشابه
Weighted gene co-expression network analysis in identification of endometrial cancer prognosis markers.
OBJECTIVE Endometrial cancer (EC) is the most common gynecologic malignancy. Identification of potential biomarkers of EC would be helpful for the detection and monitoring of malignancy, improving clinical outcomes. METHODS The Weighted Gene Co-expression Network Analysis method was used to identify prognostic markers for EC in this study. Moreover, underlying molecular mechanisms were charac...
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Introduction: HER2-enriched subtype of breast cancer has a worse prognosis than luminal subtypes. Recently, the discovery of targeted therapies in other groups of breast cancer has increased patient survival. The aim of this study was to identify genes that affect the overall survival of this group of patients based on a systems biology approach. Methods: Gene expression data and clinical infor...
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اندیشمندان و صاحب نظران علوم اجتماعی بر این باورند که مرحله تازه ای در تاریخ جوامع بشری اغاز شده است. ویژگیهای این جامعه نو را می توان پدیده هایی از جمله اقتصاد اطلاعاتی جهانی ، هندسه متغیر شبکه ای، فرهنگ مجاز واقعی ، توسعه حیرت انگیز فناوری های دیجیتال، خدمات پیوسته و نیز فشردگی زمان و مکان برشمرد. از سوی دیگر قدرت به عنوان موضوع اصلی علم سیاست جایگاه مهمی در روابط انسانی دارد، قدرت و بازتولید...
15 صفحه اولMODA: MOdule Differential Analysis for weighted gene co-expression network
Gene co-expression network differential analysis is designed to help biologists understand gene expression patterns under different conditions. We have implemented an R package called MODA (Module Differential Analysis) for gene co-expression network differential analysis. Based on transcriptomic data, MODA can be used to estimate and construct condition-specific gene co-expression networks, an...
متن کاملA general framework for weighted gene co-expression network analysis.
Gene co-expression networks are increasingly used to explore the system-level functionality of genes. The network construction is conceptually straightforward: nodes represent genes and nodes are connected if the corresponding genes are significantly co-expressed across appropriately chosen tissue samples. In reality, it is tricky to define the connections between the nodes in such networks. An...
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ژورنال
عنوان ژورنال: Asian Pacific Journal of Cancer Prevention
سال: 2012
ISSN: 1513-7368
DOI: 10.7314/apjcp.2012.13.9.4607