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RECOMB
2002
Springer
16 years 6 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...
185
Voted
TMI
2010
175views more  TMI 2010»
15 years 26 days ago
Spatially Adaptive Mixture Modeling for Analysis of fMRI Time Series
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In [1, 2...
Thomas Vincent, Laurent Risser, Philippe Ciuciu
SIGPRO
2008
136views more  SIGPRO 2008»
15 years 6 months ago
Estimation of slowly varying parameters in nonlinear systems via symbolic dynamic filtering
This paper introduces a novel method for real-time estimation of slowly varying parameters in nonlinear dynamical systems. The core concept is built upon the principles of symboli...
Venkatesh Rajagopalan, Subhadeep Chakraborty, Asok...
139
Voted
AMC
2006
79views more  AMC 2006»
15 years 6 months ago
VC-dimension and structural risk minimization for the analysis of nonlinear ecological models
The problem of distinguishing density-independent (DI) from density-dependent (DD) demographic time series is important for understanding the mechanisms that regulate populations ...
Giorgio Corani, Marino Gatto
SBRN
2008
IEEE
16 years 16 days ago
Selecting Neural Network Forecasting Models Using the Zoomed-Ranking Approach
In this work, we propose to use the Zoomed-Ranking approach to ranking and selecting Artificial Neural Network (ANN) models for time series forecasting. Given a time series to fo...
Patrícia M. Santos, Teresa Bernarda Ludermi...