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BMCBI
2006
98views more  BMCBI 2006»
13 years 7 months ago
In search of functional association from time-series microarray data based on the change trend and level of gene expression
Background: The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional l...
Feng He, An-Ping Zeng
ISBI
2009
IEEE
14 years 2 months ago
Detecting Maximal Directional Changes in Spatial fMRI Response Using Canonical Correlation Analysis
Traditional fMRI analysis has focused on modeling temporal changes in BOLD signals on a voxel-by-voxel basis to infer brain activation. To incorporate spatial information, we have...
Bernard Ng, Rafeef Abugharbieh, Martin McKeown
BMCBI
2007
198views more  BMCBI 2007»
13 years 7 months ago
Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation
Time course gene expression experiments are a popular means to infer co-expression. Many methods have been proposed to cluster genes or to build networks based on similarity measu...
Nicola Neretti, Daniel Remondini, Marc Tatar, John...
ICAI
2008
13 years 8 months ago
Mapping of Activity Recognition as a Distributed Inference Problem in Sensor Network
- This paper presents a distributed model for detecting Activities of Daily Living (ADLs) in a home setting. We consider an environment where household devices and utensils are aug...
Md. Kamrul Hasan, Husne Ara Rubaiyeat, Young-Koo L...
NIPS
2008
13 years 8 months ago
Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM
Neural activity is non-stationary and varies across time. Hidden Markov Models (HMMs) have been used to track the state transition among quasi-stationary discrete neural states. W...
Kentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Ma...