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Identifying and Analyzing Novel Epilepsy-Related Genes Using Random Walk with Restart Algorithm
المؤلفون المشاركون
Jiang, Yang
Gao, Yu-Fei
Feng, Kaiyan
Wang, ShaoPeng
Guo, Wei
Shang, Dong-Mei
Cao, Jing-Hui
He, Yi-Chun
المصدر
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-02-01
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
As a pathological condition, epilepsy is caused by abnormal neuronal discharge in brain which will temporarily disrupt the cerebral functions.
Epilepsy is a chronic disease which occurs in all ages and would seriously affect patients’ personal lives.
Thus, it is highly required to develop effective medicines or instruments to treat the disease.
Identifying epilepsy-related genes is essential in order to understand and treat the disease because the corresponding proteins encoded by the epilepsy-related genes are candidates of the potential drug targets.
In this study, a pioneering computational workflow was proposed to predict novel epilepsy-related genes using the random walk with restart (RWR) algorithm.
As reported in the literature RWR algorithm often produces a number of false positive genes, and in this study a permutation test and functional association tests were implemented to filter the genes identified by RWR algorithm, which greatly reduce the number of suspected genes and result in only thirty-three novel epilepsy genes.
Finally, these novel genes were analyzed based upon some recently published literatures.
Our findings implicate that all novel genes were closely related to epilepsy.
It is believed that the proposed workflow can also be applied to identify genes related to other diseases and deepen our understanding of the mechanisms of these diseases.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Guo, Wei& Shang, Dong-Mei& Cao, Jing-Hui& Feng, Kaiyan& He, Yi-Chun& Jiang, Yang…[et al.]. 2017. Identifying and Analyzing Novel Epilepsy-Related Genes Using Random Walk with Restart Algorithm. BioMed Research International،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1137961
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Guo, Wei…[et al.]. Identifying and Analyzing Novel Epilepsy-Related Genes Using Random Walk with Restart Algorithm. BioMed Research International No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1137961
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Guo, Wei& Shang, Dong-Mei& Cao, Jing-Hui& Feng, Kaiyan& He, Yi-Chun& Jiang, Yang…[et al.]. Identifying and Analyzing Novel Epilepsy-Related Genes Using Random Walk with Restart Algorithm. BioMed Research International. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1137961
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1137961
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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