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» On Timed Models of Gene Networks
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BMCBI
2010
150views more  BMCBI 2010»
13 years 5 months ago
Kernel based methods for accelerated failure time model with ultra-high dimensional data
Background: Most genomic data have ultra-high dimensions with more than 10,000 genes (probes). Regularization methods with L1 and Lp penalty have been extensively studied in survi...
Zhenqiu Liu, Dechang Chen, Ming Tan, Feng Jiang, R...
FGCN
2008
IEEE
155views Communications» more  FGCN 2008»
13 years 9 months ago
Modeling the Marginal Distribution of Gene Expression with Mixture Models
We report the results of fitting mixture models to the distribution of expression values for individual genes over a broad range of normal tissues, which we call the marginal expr...
Edward Wijaya, Hajime Harada, Paul Horton
GECCO
1999
Springer
130views Optimization» more  GECCO 1999»
14 years 3 days ago
Heterochrony and Adaptation in Developing Neural Networks
This paper discusses the simulation results of a model of biological development for neural networks based on a regulatory genome. The model’s results are analyzed using the fra...
Angelo Cangelosi
IJCNN
2000
IEEE
14 years 6 days ago
Evolving Neural Network Structures Using Axonal Growth Mechanisms
In the eld of arti cial evolution creating methods to evolve neural networks is an important goal. But how to encode the structure and properties of the neural network in the geno...
Peter Eggenberger
CPM
2004
Springer
108views Combinatorics» more  CPM 2004»
14 years 1 months ago
Quadratic Time Algorithms for Finding Common Intervals in Two and More Sequences
A popular approach in comparative genomics is to locate groups or clusters of orthologous genes in multiple genomes and to postulate functional association between the genes contai...
Thomas Schmidt, Jens Stoye