Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
In this paper, we present a functional partitioning method for low power real-time distributed embedded systems whose constituent nodes are systems-on-a-chip (SOCs). The systemlev...
Computational protein design can be formulated as an optimization problem, where the objective is to identify the sequence of amino acids that minimizes the energy of a given prot...
Noah Ollikainen, Ellen Sentovich, Carlos Coelho, A...
Background: The search for enriched features has become widely used to characterize a set of genes or proteins. A key aspect of this technique is its ability to identify correlati...