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Pathogenic Network Analysis Predicts Candidate Genes for Cervical Cancer
المؤلفون المشاركون
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-02-29
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
Purpose.
The objective of our study was to predicate candidate genes in cervical cancer (CC) using a network-based strategy and to understand the pathogenic process of CC.
Methods.
A pathogenic network of CC was extracted based on known pathogenic genes (seed genes) and differentially expressed genes (DEGs) between CC and normal controls.
Subsequently, cluster analysis was performed to identify the subnetworks in the pathogenic network using ClusterONE.
Each gene in the pathogenic network was assigned a weight value, and then candidate genes were obtained based on the weight distribution.
Eventually, pathway enrichment analysis for candidate genes was performed.
Results.
In this work, a total of 330 DEGs were identified between CC and normal controls.
From the pathogenic network, 2 intensely connected clusters were extracted, and a total of 52 candidate genes were detected under the weight values greater than 0.10.
Among these candidate genes, VIM had the highest weight value.
Moreover, candidate genes MMP1, CDC45, and CAT were, respectively, enriched in pathway in cancer, cell cycle, and methane metabolism.
Conclusion.
Candidate pathogenic genes including MMP1, CDC45, CAT, and VIM might be involved in the pathogenesis of CC.
We believe that our results can provide theoretical guidelines for future clinical application.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhang, Yun-Xia& Zhao, Yan-Li. 2016. Pathogenic Network Analysis Predicts Candidate Genes for Cervical Cancer. Computational and Mathematical Methods in Medicine،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1100104
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhang, Yun-Xia& Zhao, Yan-Li. Pathogenic Network Analysis Predicts Candidate Genes for Cervical Cancer. Computational and Mathematical Methods in Medicine No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1100104
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhang, Yun-Xia& Zhao, Yan-Li. Pathogenic Network Analysis Predicts Candidate Genes for Cervical Cancer. Computational and Mathematical Methods in Medicine. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1100104
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1100104
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
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