Predict and Analyze Protein Glycation Sites with the mRMR and IFS Methods

المؤلفون المشاركون

Wang, Jia-Nan
Zhang, Wen-yi
Liu, Yan
Gu, Wenxiang

المصدر

BioMed Research International

العدد

المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-6، 6ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2015-04-15

دولة النشر

مصر

عدد الصفحات

6

التخصصات الرئيسية

الطب البشري

الملخص EN

Glycation is a nonenzymatic process in which proteins react with reducing sugar molecules.

The identification of glycation sites in protein may provide guidelines to understand the biological function of protein glycation.

In this study, we developed a computational method to predict protein glycation sites by using the support vector machine classifier.

The experimental results showed that the prediction accuracy was 85.51% and an overall MCC was 0.70.

Feature analysis indicated that the composition of k -spaced amino acid pairs feature contributed the most for glycation sites prediction.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Liu, Yan& Gu, Wenxiang& Zhang, Wen-yi& Wang, Jia-Nan. 2015. Predict and Analyze Protein Glycation Sites with the mRMR and IFS Methods. BioMed Research International،Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1055917

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Liu, Yan…[et al.]. Predict and Analyze Protein Glycation Sites with the mRMR and IFS Methods. BioMed Research International No. 2015 (2015), pp.1-6.
https://search.emarefa.net/detail/BIM-1055917

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Liu, Yan& Gu, Wenxiang& Zhang, Wen-yi& Wang, Jia-Nan. Predict and Analyze Protein Glycation Sites with the mRMR and IFS Methods. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1055917

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1055917