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» Reconstructing networks using co-temporal functions
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RECOMB
2012
Springer
11 years 9 months ago
Simultaneous Reconstruction of Multiple Signaling Pathways via the Prize-Collecting Steiner Forest Problem
Signaling networks are essential for cells to control processes such as growth and response to stimuli. Although many “omic” data sources are available to probe signaling pathw...
Nurcan Tuncbag, Alfredo Braunstein, Andrea Pagnani...
BMCBI
2010
119views more  BMCBI 2010»
13 years 7 months ago
Functional classification of proteins based on projection of amino acid sequences: application for prediction of protein kinase
Background: The knowledge about proteins with specific interaction capacity to the protein partners is very important for the modeling of cell signaling networks. However, the exp...
Boris Sobolev, Dmitry Filimonov, Alexey Lagunin, A...
ICIP
2004
IEEE
14 years 9 months ago
Distributed compression of the plenoptic function
In this paper, we consider the problem of distributed compression in camera sensor networks. Due to the spatial proximity of the different cameras, acquired images can be highly d...
Nicolas Gehrig, Pier Luigi Dragotti
ICMLA
2007
13 years 8 months ago
Maximum Likelihood Quantization of Genomic Features Using Dynamic Programming
Dynamic programming is introduced to quantize a continuous random variable into a discrete random variable. Quantization is often useful before statistical analysis or reconstruct...
Mingzhou (Joe) Song, Robert M. Haralick, Sté...
ICANN
2010
Springer
13 years 7 months ago
Deep Bottleneck Classifiers in Supervised Dimension Reduction
Deep autoencoder networks have successfully been applied in unsupervised dimension reduction. The autoencoder has a "bottleneck" middle layer of only a few hidden units, ...
Elina Parviainen