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
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