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...
Background: A widely-used approach for discovering functional and physical interactions among proteins involves phylogenetic profile comparisons (PPCs). Here, proteins with simila...
Background: In binary high-throughput screening projects where the goal is the identification of low-frequency events, beyond the obvious issue of efficiency, false positives and ...
Over the past few years, swarm based systems have emerged as an attractive paradigm for building large scale distributed systems composed of numerous independent but coordinating ...
Matthew Hoeing, Prithviraj Dasgupta, Plamen V. Pet...
Graphical models are a framework for representing and exploiting prior conditional independence structures within distributions using graphs. In the Gaussian case, these models are...