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Statistical pattern recognition techniques classify objects in terms of a representative set of features. The selection of features to measure and include can have a significant effect on the cost and accuracy of an automated classifier. Our previous research has shown that a hybrid between a k-nearest-neighbors (knn) classifier and a genetic algorithm (GA)(More)
A key element of bioinformatics research is the extraction of meaningful information from large experimental data sets. Various approaches, including statistical and graph theoretical methods, data mining, and computational pattern recognition, have been applied to this task with varying degrees of success. Using a novel classifier based on the Bayes(More)
Water-mediated ligand interactions are essential to biological processes, from product displacement in thymidylate synthase to DNA recognition by Trp repressor, yet the structural chemistry influencing whether bound water is displaced or participates in ligand binding is not well characterized. Consolv, employing a hybrid k-nearest-neighbors(More)
Bioinformatics is a new and rapidly evolving discipline that has emerged from the fields of experimental molecular biology and biochemistry, and from the the artificial intelligence, database, and algorithms disciplines of computer science. Largely because of the inherently interdisciplinary nature of bioinformatics research, academia has been slow to(More)
– Bioinformatics is a new and rapidly evolving discipline that has emerged from the fields of experimental molecular biology and biochemistry, and from the the artificial intelligence, database, pattern recognition, and algorithms disciplines of computer science. Largely because of the inherently interdisciplinary nature of bioinformatics research, academia(More)
Prokaryotic organisms preferentially utilize less energetically costly amino acids in highly expressed genes. Studies have shown that the proteome of Saccharomyces cerevisiae also exhibits this behavior, but only in broad terms. This study examines the question of metabolic efficiency as a proteome-shaping force at a finer scale, examining whether trends(More)
The authors present a GA optimization technique for cosine-based k-nearest neighbors classification that improves predictive accuracy in a class-balanced manner while simultaneously enabling knowledge discovery. The GA performs feature selection and extraction by searching for feature weights and offsets maximizing cosine classifier performance. GA-selected(More)
Samples containing DNA from two or more individuals can be difficult to interpret. Even ascertaining the number of contributors can be challenging and associated uncertainties can have dramatic effects on the interpretation of testing results. Using an FBI genotypes dataset, containing complete genotype information from the 13 Combined DNA Index System(More)