Comment on causality and pathway search in microarray time series experiment

Bioinformatics

Volumn 24, Issue 7, 2008, Pages 1029-1032

  Nagarajan, Radhakrishnan ^a   Upreti, Meenakshi ^a  

^a UNIVERSITY OF ARKANSAS FOR MEDICAL SCIENCES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOINFORMATICS; BIOSTATISTICS; GENE EXPRESSION PROFILING; GENETIC TRANSCRIPTION; GENETIC VARIABILITY; MATHEMATICAL ANALYSIS; MICROARRAY ANALYSIS; NOTE; PRIORITY JOURNAL; TIME SERIES ANALYSIS;

ALGORITHMS; COMPUTER SIMULATION; GENE EXPRESSION PROFILING; MODELS, BIOLOGICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PROTEOME; SIGNAL TRANSDUCTION; TIME FACTORS;

EID: 41349085815     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btm586     Document Type: Note

References (6)

1. Fujita,A. et al. (2007) Time-varying modeling of gene expression regulatory networks using the wavelet dynamic vector autoregressive method. Bioinformatics, 23, 1623-1630.
2. Granger,C.W.J. (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica., 37, 424-438.
3. Hamilton,J.D. (1994) Time Series Analysis. Princeton University press, Princeton, NJ.
4. Mukhopadhyay,N.D. and Chatterjee,S. (2007) Causality and pathway search in microarray time series experiment. Bioinformatics, 23, 442-449.
5. Opgen-Rhein,R. and Strimmer,K. (2007) Learning causal networks from systems biology time course data: An effective model selection procedure for the vector autoregressive process. BMC Bioinformatics, 8 (Suppl. 2), S3.
6. Speed,T. (2003) Statistical Analysis of Gen Expression Microarray Data. Chapman & Hall/CRC, USA.