PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-1 (1)
 

Clipboard (0)
None
Journals
Authors
Year of Publication
Document Types
1.  Prediction of Enzyme Mutant Activity Using Computational Mutagenesis and Incremental Transduction 
Advances in Bioinformatics  2011;2011:958129.
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.
doi:10.1155/2011/958129
PMCID: PMC3189455  PMID: 22007208

Results 1-1 (1)