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» Analyzing time series gene expression data
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IJON
2008
128views more  IJON 2008»
13 years 5 months ago
Independent arrays or independent time courses for gene expression time series data analysis
In this paper we apply three different independent component analysis (ICA) methods, including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA), to gene exp...
Sookjeong Kim, Jong Kyoung Kim, Seungjin Choi
TCSB
2008
13 years 5 months ago
Clustering Time-Series Gene Expression Data with Unequal Time Intervals
Clustering gene expression data given in terms of time-series is a challenging problem that imposes its own particular constraints, namely exchanging two or more time points is not...
Luis Rueda, Ataul Bari, Alioune Ngom
BIBE
2003
IEEE
121views Bioinformatics» more  BIBE 2003»
13 years 10 months ago
Time Series Analysis of Gene Expression and Location Data
We develop a method for integrating time series expression profiles and factor-gene binding data to quantify dynamic aspects of gene regulation. We estimate latencies for transcr...
Chen-Hsiang Yeang, Tommi Jaakkola
BMCBI
2007
139views more  BMCBI 2007»
13 years 5 months ago
Significance analysis of microarray transcript levels in time series experiments
Background: Microarray time series studies are essential to understand the dynamics of molecular events. In order to limit the analysis to those genes that change expression over ...
Barbara Di Camillo, Gianna Toffolo, Sreekumaran K....
BMCBI
2006
239views more  BMCBI 2006»
13 years 5 months ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...