Computationally identifying transcription factor binding sites in the promoter regions of genes is an important problem in computational biology and has been under intensive resea...
Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms,includ...
Tommi Jaakkola, Michael I. Jordan, Satinder P. Sin...
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Clustering methods for data-mining problems must be extremely scalable. In addition, several data mining applications demand that the clusters obtained be balanced, i.e., be of ap...
This paper presents a novel modeling algorithm that is capable of simultaneously recovering correct shape geometry as well as its unknown topology from arbitrarily complicated dat...