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Protein model assessment via machine learning techniques
by Anjum Reyaz-Ahmed, Robert Harrison, Yan-Qing Zhang
International Journal of Functional Informatics and Personalised Medicine (IJFIPM), Vol. 3, No. 3, 2010

 

Abstract: We attempt to solve the problem of protein model assessment using machine learning techniques and information from sequence and structure of the protein. The goal is to generate a machine that understands structures from PDB and given a new model, predicts whether or not it belongs to the class of PDB structures. We show two such machines (SVM and FDT); results appear promising for further analysis. To reduce computational overhead, multiprocessor environment and basic feature selection method is used. The prediction accuracy using improved FDT is above 80% and results are better when compared with other machine learning techniques.

Online publication date: Thu, 17-Mar-2011

 

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