We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Background: Many protein sequences are still poorly annotated. Functional characterization of a protein is often improved by the identification of its interaction partners. Here, ...
Andreas Henschel, Christof Winter, Wan Kyu Kim, Mi...
Background: With the rapid expansion of DNA sequencing databases, it is now feasible to identify relevant information from prior sequencing projects and completed genomes and appl...
This paper describes work in progress to develop a standard for interoperability among high-performance scientific components. This research stems from growing recognition that th...
Robert C. Armstrong, Dennis Gannon, Al Geist, Kata...
We propose a new unsupervised learning technique for extracting information about authors and topics from large text collections. We model documents as if they were generated by a...
Michal Rosen-Zvi, Chaitanya Chemudugunta, Thomas L...