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Prediction of Enzyme Mutant Activity Using Computational Mutagenesis and Incremental Transduction
Joint Authors
Source
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-10-09
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Natural & Life Sciences (Multidisciplinary)
Biology
Abstract EN
Wet laboratory mutagenesis to determine enzyme activity changes is expensive and time consuming.
This paper expands on standard one-shot learning by proposing an incremental transductive method (T2bRF) for the prediction of enzyme mutant activity during mutagenesis using Delaunay tessellation and 4-body statistical potentials for representation.
Incremental learning is in tune with both eScience and actual experimentation, as it accounts for cumulative annotation effects of enzyme mutant activity over time.
The experimental results reported, using cross-validation, show that overall the incremental transductive method proposed, using random forest as base classifier, yields better results compared to one-shot learning methods.
T2bRF is shown to yield 90% on T4 and LAC (and 86% on HIV-1).
This is significantly better than state-of-the-art competing methods, whose performance yield is at 80% or less using the same datasets.
American Psychological Association (APA)
Basit, Nada& Wechsler, Harry. 2011. Prediction of Enzyme Mutant Activity Using Computational Mutagenesis and Incremental Transduction. Advances in Bioinformatics،Vol. 2011, no. 2011, pp.1-9.
https://search.emarefa.net/detail/BIM-511407
Modern Language Association (MLA)
Basit, Nada& Wechsler, Harry. Prediction of Enzyme Mutant Activity Using Computational Mutagenesis and Incremental Transduction. Advances in Bioinformatics No. 2011 (2011), pp.1-9.
https://search.emarefa.net/detail/BIM-511407
American Medical Association (AMA)
Basit, Nada& Wechsler, Harry. Prediction of Enzyme Mutant Activity Using Computational Mutagenesis and Incremental Transduction. Advances in Bioinformatics. 2011. Vol. 2011, no. 2011, pp.1-9.
https://search.emarefa.net/detail/BIM-511407
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-511407