id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_xvokgoinujc6dfyjg4yqhyecqu	Wiesław Chmielnicki	An improved protein fold recognition with support vector machines	2010	10	.pdf	application/pdf	4933	493	58	A novel feature fusion based on the evolutionary features for protein fold recognition using support vector machines extracting features from protein sequences and using a strong classifier. In this study, we integrate Auto-Cross-Covariance (ACC) and Separated dimer (SD) evolutionary feature extraction According to three benchmark datasets, DD, RDD and EDD, the results of the support vector machine (SVM) show Keywords: Protein Fold Recognition, Feature fusion, Evolutionary method, IG, Support Vector Machine vital stage for predicting protein fold is feature extraction. methods of protein fold recognition, we found that less attention has been paid to the fusion of features to get more features, we use Auto-Cross-Covariance(ACC)[8] and Separated dimer(SD)[7] methods. extraction methods based on Position Specific Scoring Matrix(PSSM) generated by using the Position-Specific Iterated BLAST(PSI-BLAST) profile to predict protein fold. extraction technique using bi-gram probabilities of position specific scoring matrix for protein fold recognition, Journal of theoretical biology 320 (2013) 41–46.	./cache/work_xvokgoinujc6dfyjg4yqhyecqu.pdf	./txt/work_xvokgoinujc6dfyjg4yqhyecqu.txt