DocumentCode :
2341159
Title :
Automated Identifying Intrinsic Unstructured Regions in Proteins - A Software Tool
Author :
Yang, Jack Y. ; Qu Yang, M. ; Zuojie Luo ; Ersoy, Okan
Author_Institution :
Harvard Med. Sch., Harvard Univ., Boston, MA
fYear :
0
fDate :
0-0 0
Firstpage :
1
Lastpage :
4
Abstract :
In our attempts to construct methods for automated structural and functional annotation of proteins, the prediction of intrinsically unstructured/disordered protein (IUP) regions, i.e. those with a lack of stable secondary or tertiary structure, has recently gained importance. We developed a software tool for identifying IUP and structured protein regions. The predictor uses both supervised and unsupervised learning techniques and both structural and motional information of amino acids. We demonstrate the effectiveness of our IUP predictor which utilizes feature selection, bootstrapping aggregation, boosting and consensus networking algorithms
Keywords :
biology computing; learning (artificial intelligence); proteins; IUP predictor; amino acids; automated identification; bioinformatics; bootstrapping aggregation; computational intelligence; data mining; feature selection; intrinsic unstructured regions; intrinsically unstructured/disordered protein; knowledge discovery; membrane proteins; networking algorithms; software tool; structured protein regions; supervised learning; unsupervised learning techniques; Amino acids; Bioinformatics; Boosting; Buildings; Classification tree analysis; Genomics; Lifting equipment; Protein engineering; Software tools; USA Councils; Bioinformatics; classification and knowledge discovery; data mining and computational intelligence; intrinsic unstructured proteins; membrane proteins;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence Methods and Applications, 2005 ICSC Congress on
Conference_Location :
Istanbul
Print_ISBN :
1-4244-0020-1
Type :
conf
DOI :
10.1109/CIMA.2005.1662361
Filename :
1662361
Link To Document :
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