Large amounts of protein-protein interaction data have been identified using various genome-scale screening techniques. Although interaction data is a valuable resource, high-thro...
Background: Identifying candidate genes in genetic networks is important for understanding regulation and biological function. Large gene expression datasets contain relevant info...
Anup Parikh, Eryong Huang, Christopher Dinh, Blaz ...
KBCC is an extension of the cascade-correlation algorithm that treats functions encapsulating prior knowledge as black-boxes which, like simple sigmoidal neurons, can be recruited...
Background: Tandem mass spectrometry (MS/MS) is a powerful tool for protein identification. Although great efforts have been made in scoring the correlation between tandem mass sp...
We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density func...