Relational Markov models (RMMs) are a generalization of Markov models where states can be of different types, with each type described by a different set of variables. The domain ...
The goal of the knowledge discovery and data mining is to extract the useful knowledge from the given data. Visualization enables us to find structures, features, patterns, and re...
We present a closed set data mining paradigm which is particularly e ective for uncovering the kind of deterministic, causal dependencies that characterize much of basic science. ...
The 3D conformation of a protein may be compactly represented in a symmetrical, square, boolean matrix of pairwise, inter-residue contacts, or "contact map". The contact...
Jingjing Hu, Xiaolan Shen, Yu Shao, Chris Bystroff...
This paper promotes the use of supervised machine learning in laboratory settings where chemists have a large number of samples to test for some property, and are interested in id...
Protein secondary structure prediction and high-throughput drug screen data mining are two important applications in bioinformatics. The data is represented in sparse feature spac...
Steven Eschrich, Nitesh V. Chawla, Lawrence O. Hal...