Ens-PPI: A Novel Ensemble Classifier for Predicting the Interactions of Proteins Using Autocovariance Transformation from PSSM
المؤلفون المشاركون
Xia, Shixiong
Gao, Zhen-Guo
Wang, Lei
You, Zhu-Hong
Yan, Xin
Yong, Zhou
المصدر
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-06-29
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
Protein-Protein Interactions (PPIs) play vital roles in most biological activities.
Although the development of high-throughput biological technologies has generated considerable PPI data for various organisms, many problems are still far from being solved.
A number of computational methods based on machine learning have been developed to facilitate the identification of novel PPIs.
In this study, a novel predictor was designed using the Rotation Forest (RF) algorithm combined with Autocovariance (AC) features extracted from the Position-Specific Scoring Matrix (PSSM).
More specifically, the PSSMs are generated using the information of protein amino acids sequence.
Then, an effective sequence-based features representation, Autocovariance, is employed to extract features from PSSMs.
Finally, the RF model is used as a classifier to distinguish between the interacting and noninteracting protein pairs.
The proposed method achieves promising prediction performance when performed on the PPIs of Yeast, H.
pylori, and independent datasets.
The good results show that the proposed model is suitable for PPIs prediction and could also provide a useful supplementary tool for solving other bioinformatics problems.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Gao, Zhen-Guo& Wang, Lei& Xia, Shixiong& You, Zhu-Hong& Yan, Xin& Yong, Zhou. 2016. Ens-PPI: A Novel Ensemble Classifier for Predicting the Interactions of Proteins Using Autocovariance Transformation from PSSM. BioMed Research International،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1097810
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Gao, Zhen-Guo…[et al.]. Ens-PPI: A Novel Ensemble Classifier for Predicting the Interactions of Proteins Using Autocovariance Transformation from PSSM. BioMed Research International No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1097810
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Gao, Zhen-Guo& Wang, Lei& Xia, Shixiong& You, Zhu-Hong& Yan, Xin& Yong, Zhou. Ens-PPI: A Novel Ensemble Classifier for Predicting the Interactions of Proteins Using Autocovariance Transformation from PSSM. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1097810
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1097810
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