This paper addresses the protein classification problem, and explores how its accuracy can be improved by using information from time-course gene expression data. The methods are ...
Antonina Mitrofanova, Samantha Kleinberg, Jane Car...
Recent studies in protein sequence analysis have leveraged the power of unlabeled data. For example, the profile and mismatch neighborhood kernels have shown significant improveme...
: The analysis of Biological Regulatory Network (BRN) leads to compute the set of the possible behaviours of the biological components. These behaviours are seen as trajectories an...
The evolutionary histories of viral genomes have received significant recent attention due to their importance in understanding virulence and the corresponding ramifications to pu...
We develop a parallel algorithm for a widely used whole genome alignment method called LAGAN. We use the MPI-based protocol to develop parallel solutions for two phases of the alg...
We present an EM-based clustering method that can be used for constructing or augmenting ontologies such as MeSH. Our algorithm simultaneously clusters verbs and nouns using both ...
Vasileios Kandylas, Lyle H. Ungar, Ted Sandler, Sh...
Abstract—The exact relationship between protein active centers and protein functions is unclear even after decades of intensive study. To improve the functional prediction abilit...
Protein fold recognition is the prediction of protein’s tertiary structure (Fold) given the protein’s sequence without relying on sequence similarity. Using machine learning t...
We adapt a network simulation algorithm called quantitative simulation (QSim) for use in the alignment of biological networks. Unlike most network alignment methods, QSim finds l...