Predicting Subcellular Localization of Apoptosis Proteins Combining GO Features of Homologous Proteins and Distance Weighted KNN Classifier

المؤلفون المشاركون

Wang, Xiao
Li, Hui
Wang, Rong
Zhang, Qiuwen

المصدر

BioMed Research International

العدد

المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-8، 8ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2016-04-24

دولة النشر

مصر

عدد الصفحات

8

التخصصات الرئيسية

الطب البشري

الملخص EN

Apoptosis proteins play a key role in maintaining the stability of organism; the functions of apoptosis proteins are related to their subcellular locations which are used to understand the mechanism of programmed cell death.

In this paper, we utilize GO annotation information of apoptosis proteins and their homologous proteins retrieved from GOA database to formulate feature vectors and then combine the distance weighted KNN classification algorithm with them to solve the data imbalance problem existing in CL317 data set to predict subcellular locations of apoptosis proteins.

It is found that the number of homologous proteins can affect the overall prediction accuracy.

Under the optimal number of homologous proteins, the overall prediction accuracy of our method on CL317 data set reaches 96.8% by Jackknife test.

Compared with other existing methods, it shows that our proposed method is very effective and better than others for predicting subcellular localization of apoptosis proteins.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Wang, Xiao& Li, Hui& Zhang, Qiuwen& Wang, Rong. 2016. Predicting Subcellular Localization of Apoptosis Proteins Combining GO Features of Homologous Proteins and Distance Weighted KNN Classifier. BioMed Research International،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1096968

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Wang, Xiao…[et al.]. Predicting Subcellular Localization of Apoptosis Proteins Combining GO Features of Homologous Proteins and Distance Weighted KNN Classifier. BioMed Research International No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1096968

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Wang, Xiao& Li, Hui& Zhang, Qiuwen& Wang, Rong. Predicting Subcellular Localization of Apoptosis Proteins Combining GO Features of Homologous Proteins and Distance Weighted KNN Classifier. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1096968

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1096968