Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
With the exponential growth of complete genome sequences, the analysis of these sequences is becoming a powerful approach to build genome-scale metabolic models. These models can ...
Background: Several aspects of microarray data analysis are dependent on identification of genes expressed at or near the limits of detection. For example, regression-based normal...
Igor Dozmorov, Nicholas Knowlton, Yuhong Tang, Mic...
Grid services have tremendously simplified the programming challenges in leveraging large-scale distributed comAt the same time, the increased level of abstraction reduces the op...
Radio Frequency (RF) tomography refers to the process of inferring information about an environment by capturing and analyzing RF signals transmitted between nodes in a wireless se...