Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
Background: Genotype information generated by individual and international efforts carries the promise of revolutionizing disease studies and the association of phenotypes with al...
Background: Gene function analysis often requires a complex and laborious sequence of laboratory and computer-based experiments. Choosing an effective experimental design generall...
Oliver Laule, Matthias Hirsch-Hoffmann, Tomas Hruz...
Background -: Sequencing of EST and BAC end datasets is no longer limited to large research groups. Drops in per-base pricing have made high throughput sequencing accessible to in...
Stephen E. Diener, Thomas D. Houfek, Sam E. Kalat,...