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Protein Secondary Structure Prediction using fuzzy multi-class support vector data

عنوان مقاله: Protein Secondary Structure Prediction using fuzzy multi-class support vector data
شناسه ملی مقاله: ICEEE07_643
منتشر شده در هفتمین کنفرانس ملی مهندسی برق و الکترونیک ایران در سال 1394
مشخصات نویسندگان مقاله:

Hooman Kashanian - Islamic Azad University Ferdows, Iran
Hamid reza Ghaffary - Islamic Azad University Ferdows, Iran
javad Sadri - McGill University Montreal, Canada
Mahmoud Sadoughi - Islamic Azad University Gonabad, Iran

خلاصه مقاله:
A flood of data means that many of the challenges in biology are now challenges in computing. In modern computation biology, research of protein secondary structure plays a major role in protein tertiary structure prediction. Protein structure prediction is depends on its amino acid sequence. In this report we will first review multi-class classification methods base on support vector machine. In the following paper using a fuzzy support vector data description (SVDD) to Prediction Protein structure secondary. In the context of Protein Secondary Structure Prediction (PSSP), prediction” carries similar meaning as that of classification by study recent researches in new methods that improved classification fuzzy SVDD and we could use these methods in (PSSP)

کلمات کلیدی:
Protein Secondary Structure Prediction, fuzzy support vector data description

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/459627/