We study the problem of finding the dominant eigenvector of the sample covariance matrix, under additional constraints on the vector: a cardinality constraint limits the number of...
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
Clustering problems often involve datasets where only a part of the data is relevant to the problem, e.g., in microarray data analysis only a subset of the genes show cohesive exp...
Background: There is great interest in probing the temporal and spatial patterns of cytosine methylation states in genomes of a variety of organisms. It is hoped that this will sh...
Eyal Gruntman, Yijun Qi, R. Keith Slotkin, Ted Roe...
Background: Analysis of sequence composition is a routine task in genome research. Organisms are characterized by their base composition, dinucleotide relative abundance, codon us...