We present ARACNE, a novel algorithm, using microarray expression profiles, specifically designed to scale up to the complexity of regulatory networks in mammalian cells, yet general enough to address a wider range of network deconvolution problems.Expand

We study properties of popular near–uniform (Dirichlet) priors for learning undersampled probability distributions on discrete nonmetric spaces and show that they lead to disastrous results.Expand

Noise limits information transfer through a single signaling pathway in a single cell to just one bit. Molecular noise restricts the ability of an individual cell to resolve input signals of… Expand

The major problem in information theoretic analysis of neural responses and other biological data is the reliable estimation of entropy-like quantities from small samples, where other techniques fail.Expand

The problem of defining and studying complexity of a time series has interested people for years. In the context of dynamical systems, Grassberger has suggested that a slow approach of the entropy to… Expand

We have found that under natural stimulus conditions the fly visual system generates spikes and interspike intervals with extraordinary temporal precision.Expand

We define the concept of dependence among multiple variables using maximum entropy techniques and introduce a graphical notation to denote the dependencies.Expand

We perform an asymptotic analysis of the NSB estimator of entropy of a discrete random variable and show that the estimator has a non-trivial limit for a large cardinality of the studied variable.Expand

We show that, with cross-talk, concentration of more than one chemical species can be inferred from one receptor, provided that the stochastic temporal sequence of receptor binding and unbinding events is accessible instead of its mean occupancy.Expand

We define predictive information as the mutual information between the past and the future of a time series, discuss its behavior as a function of the length of the series, and explain how other quantities of interest studied previously in learning theory emerge from this universally definable concept.Expand