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BMCBI
2006
98views more  BMCBI 2006»
14 years 9 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
15 years 4 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»
14 years 9 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
14 years 11 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
14 years 10 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...