Prediction of disulfide connectivity in proteins with machine-learning methods and correlated mutations

被引：0
|
作者：
Savojardo, Castrense [1 ,2 ]
Fariselli, Piero [1 ,2 ]
Martelli, Pier Luigi [2 ,3 ]
Casadio, Rita [2 ,3 ]
机构：
[1] Department of Computer Science and Engineering, University of Bologna, Via Mura Anteo Zamboni 7, 41029 Bologna, Italy
[2] Biocomputing Group, University of Bologna, via Selmi 3, 40126 Bologna, Italy
[3] CIRI-Life Science and Health Technologies/Department of Biology, Via San Giacomo 9/2, 40129, Bologna, Italy
来源：
BMC Bioinformatics | 2013年 / 14卷 / SUPPL.1期
关键词：
Disulfide connectivities - Evolutionary information - Machine learning methods - Multiple sequence alignments - Scoring performance - State-of-the-art methods - Statistical validation - Support vector regression (SVR);
D O I：
S10
中图分类号：
学科分类号：
摘要：
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