Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.
Pipeline for large-scale genome changes analysis of genome datasets.
The active use repository has migrated over to: https://github.com/darrenabbey/ymap The repository here was errantly created with some large binary files included. Attempts to extract the files from the history here have failed. A copy of the history was successfully scrubbed and then hosted at github. -------- Eukaryotic pathogens have complicated and dynamic genomes. To facilitate analysis of copy number variations (CNV), single nucleotide polymorphisms (SNPs), and loss of heterozygosity (LOH) events in Candida albicans, the most common human fungal pathogen, we developed a pipeline for analyzing diverse genome-scale datasets from microarray, deep sequencing, and restriction site associated DNA sequence experiments for clinical and laboratory strains. The YMAP pipeline automatically illustrates genome-wide information in a single intuitive figure and is readily modified for the analysis of other categories of data and other pathogen species with small genomes.