Predicting Metabolite-Disease Associations Based on Linear Neighborhood Similarity with Improved Bipartite Network Projection Algorithm
المؤلفون المشاركون
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-05-23
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
A large number of clinical observations have showed that metabolites are involved in a variety of important human diseases in the recent years.
Nonetheless, the inherent noise and incompleteness in the existing biological datasets are tough factors which limit the prediction accuracy of current computational methods.
To solve this problem, in this paper, a prediction method, IBNPLNSMDA, is proposed which uses the improved bipartite network projection method to predict latent metabolite-disease associations based on linear neighborhood similarity.
Specifically, liner neighborhood similarity matrix about metabolites (diseases) is reconstructed according to the new feature which is gained by the known metabolite-disease associations and relevant integrated similarities.
The improved bipartite network projection method is adopted to infer the potential associations between metabolites and diseases.
At last, IBNPLNSMDA achieves a reliable performance in LOOCV (AUC of 0.9634) outperforming the compared methods.
In addition, in case studies of four common human diseases, simulation results confirm the utility of our method in discovering latent metabolite-disease pairs.
Thus, we believe that IBNPLNSMDA could serve as a reliable computational tool for metabolite-disease associations prediction.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Lei, Xiujuan& Zhang, Cheng. 2020. Predicting Metabolite-Disease Associations Based on Linear Neighborhood Similarity with Improved Bipartite Network Projection Algorithm. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1145536
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Lei, Xiujuan& Zhang, Cheng. Predicting Metabolite-Disease Associations Based on Linear Neighborhood Similarity with Improved Bipartite Network Projection Algorithm. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1145536
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Lei, Xiujuan& Zhang, Cheng. Predicting Metabolite-Disease Associations Based on Linear Neighborhood Similarity with Improved Bipartite Network Projection Algorithm. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1145536
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1145536
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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