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RECOMB
2002
Springer
16 years 5 months ago
A new approach to analyzing gene expression time series data
We present algorithms for time-series gene expression analysis that permit the principled estimation of unobserved timepoints, clustering, and dataset alignment. Each expression p...
Ziv Bar-Joseph, Georg Gerber, David K. Gifford, To...
BMCBI
2004
169views more  BMCBI 2004»
15 years 5 months ago
A power law global error model for the identification of differentially expressed genes in microarray data
Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...
SDM
2007
SIAM
104views Data Mining» more  SDM 2007»
15 years 6 months ago
Boosting Optimal Logical Patterns Using Noisy Data
We consider the supervised learning of a binary classifier from noisy observations. We use smooth boosting to linearly combine abstaining hypotheses, each of which maps a subcube...
Noam Goldberg, Chung-chieh Shan
RTSS
1998
IEEE
15 years 9 months ago
The Time-Triggered Model of Computation
: The Time-Triggered (TT) model of computation is a model for the representation and analysis of the design of large hard real-time systems. Central to this model is the concept of...
Hermann Kopetz
CORR
2007
Springer
170views Education» more  CORR 2007»
15 years 5 months ago
The structure of verbal sequences analyzed with unsupervised learning techniques
Data mining allows the exploration of sequences of phenomena, whereas one usually tends to focus on isolated phenomena or on the relation between two phenomena. It offers invaluab...
Catherine Recanati, Nicoleta Rogovschi, Youn&egrav...