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» Learning patterns in the dynamics of biological networks
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CONNECTION
2006
101views more  CONNECTION 2006»
13 years 7 months ago
High capacity, small world associative memory models
Models of associative memory usually have full connectivity or if diluted, random symmetric connectivity. In contrast, biological neural systems have predominantly local, non-symm...
Neil Davey, Lee Calcraft, Rod Adams
AINA
2008
IEEE
14 years 2 months ago
Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
Connie Phong, Raul Singh
BMCBI
2007
135views more  BMCBI 2007»
13 years 7 months ago
Detecting multivariate differentially expressed genes
Background: Gene expression is governed by complex networks, and differences in expression patterns between distinct biological conditions may therefore be complex and multivariat...
Roland Nilsson, José M. Peña, Johan ...
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
14 years 1 months ago
Generating large-scale neural networks through discovering geometric regularities
Connectivity patterns in biological brains exhibit many repeating motifs. This repetition mirrors inherent geometric regularities in the physical world. For example, stimuli that ...
Jason Gauci, Kenneth O. Stanley
SIGMOD
2003
ACM
121views Database» more  SIGMOD 2003»
14 years 8 months ago
An environmental sensor network to determine drinking water quality and security
Finding patterns in large, real, spatio/temporal data continues to attract high interest (e.g., sales of products over space and time, patterns in mobile phone users; sensor netwo...
Anastassia Ailamaki, Christos Faloutsos, Paul S. F...