Now showing items 1-5 of 5
A framework for integrating the songbird brain.
(J Comp Physiol A Neuroethol Sens Neural Behav Physiol, 2002-12)
Biological systems by default involve complex components with complex relationships. To decipher how biological systems work, we assume that one needs to integrate information over multiple levels of complexity. The songbird ...
Influence of network topology and data collection on network inference.
(Pac Symp Biocomput, 2003)
We recently developed an approach for testing the accuracy of network inference algorithms by applying them to biologically realistic simulations with known network topology. Here, we seek to determine the degree to which ...
Advances to Bayesian network inference for generating causal networks from observational biological data.
MOTIVATION: Network inference algorithms are powerful computational tools for identifying putative causal interactions among variables from observational data. Bayesian network inference algorithms hold particular promise ...
Evaluating functional network inference using simulations of complex biological systems.
MOTIVATION: Although many network inference algorithms have been presented in the bioinformatics literature, no suitable approach has been formulated for evaluating their effectiveness at recovering models of complex biological ...
Computational inference of neural information flow networks.
(PLoS Comput Biol, 2006-11-24)
Determining how information flows along anatomical brain pathways is a fundamental requirement for understanding how animals perceive their environments, learn, and behave. Attempts to reveal such neural information flow ...