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RECOMB
2000
Springer
14 years 4 days ago
Using Bayesian networks to analyze expression data
DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a "snapshot" of transcription levels within the c...
Nir Friedman, Michal Linial, Iftach Nachman, Dana ...
IDA
2005
Springer
14 years 2 months ago
Bayesian Networks Learning for Gene Expression Datasets
DNA arrays yield a global view of gene expression and can be used to build genetic networks models, in order to study relations between genes. Literature proposes Bayesian network ...
Giacomo Gamberoni, Evelina Lamma, Fabrizio Riguzzi...
RECOMB
2008
Springer
14 years 8 months ago
Automatic Parameter Learning for Multiple Network Alignment
We developed Gr?mlin 2.0, a new multiple network aligner with (1) a novel scoring function that can use arbitrary features of a multiple network alignment, such as protein deletion...
Jason Flannick, Antal F. Novak, Chuong B. Do, Bala...
ESANN
2006
13 years 10 months ago
Learning for stochastic dynamic programming
Abstract. We present experimental results about learning function values (i.e. Bellman values) in stochastic dynamic programming (SDP). All results come from openDP (opendp.sourcef...
Sylvain Gelly, Jérémie Mary, Olivier...
ESANN
2004
13 years 10 months ago
Evolutionary Optimization of Neural Networks for Face Detection
For face recognition from video streams speed and accuracy are vital aspects. The first decision whether a preprocessed image region represents a human face or not is often made by...
Stefan Wiegand, Christian Igel, Uwe Handmann