Beyond element-wise interactions: Identifying complex interactions in biological processes

PLoS ONE

Volumn 4, Issue 9, 2009, Pages

  Ladroue, Christophe ^a   Guo, Shuixia ^b   Kendrick, Keith ^c   Feng, Jianfeng ^a,d  

^a UNIVERSITY OF WARWICK   (United Kingdom)

^b HUNAN NORMAL UNIVERSITY   (China)

^c BABRAHAM INSTITUTE   (United Kingdom)

^d FUDAN UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BRAIN REGION; COMPLEX FORMATION; CONTROLLED STUDY; DATA BASE; FUNGAL METABOLISM; MATHEMATICAL ANALYSIS; MICROARRAY ANALYSIS; MOLECULAR INTERACTION; NONHUMAN; REACTION ANALYSIS; SACCHAROMYCES CEREVISIAE; SIGNAL DETECTION; SIMULATION; SYSTEMS BIOLOGY; ALGORITHM; BIOLOGICAL MODEL; BIOLOGY; BRAIN; COMPUTER SIMULATION; FOURIER ANALYSIS; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; METABOLISM; METHODOLOGY; PROTEIN ANALYSIS;

SACCHAROMYCES CEREVISIAE;

SACCHAROMYCES CEREVISIAE PROTEIN;

ALGORITHMS; BRAIN; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; FOURIER ANALYSIS; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, FUNGAL; MODELS, BIOLOGICAL; MODELS, GENETIC; PROTEIN INTERACTION MAPPING; SACCHAROMYCES CEREVISIAE; SACCHAROMYCES CEREVISIAE PROTEINS; SYSTEMS BIOLOGY;

EID: 70349618454     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0006899     Document Type: Article

References (35)

1. Eichler M (2006) Graphical modelling of dynamic relationships in multivariate time series. In: Schelter B, Winterhalder M, Timmer J, eds. Handbook of Time Series Analysis, Wiley-VCH Verlage. pp 335-372.
2. Granger CWJ (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37: 424-438.
3. Granger C (1980) Testing for causality a personal viewpoint. Journal of Economic Dynamics and Control 2: 329-352.
4. Pearl J (2000) Causality: Models, Reasoning, and Inference. Cambridge University Press.
5. Gourévitch B, Bouquin-Jeannès R, Faucon G (2006) Linear and nonlinear causality between signals: methods, examples and neurophysiological applications. Biological Cybernetics 95: 349-369.
6. Wu J, Liu X, Feng J (2008) Detecting causality between different frequencies. Journal of Neuroscience Methods 167: 367-375.
7. Wiener N (1956) The theory of prediction. In: Beckenbach EF, ed. Modern mathematics for engineers, McGraw-Hill, New York, chapter 8.
8. Chen Y, Bressler SL, Ding M (2006) Frequency decomposition of conditional granger causality and application to multivariate neural field potential data. Journal of Neuroscience Methods 150: 228-237.
9. Ding M, Chen Y, Bressler SL (2006) Granger causality: Basic theory and application to neuroscience. In: Schelter B, Winterhalder M, Timmer J, eds. Handbook of Time Series Analysis: Recent Theoretical Developments and Applications, Wiley-VCH, chapter 17.
10. Geweke J (1982) Measurement of linear dependence and feedback between multiple time series. Journal of the American Statistical Association 77: 304-313.
11. Geweke JF (1984) Measures of conditional linear dependence and feedback between time series. Journal of the American Statistical Association 79: 907-915.
12. Guo S, Wu J, Ding M, Feng J (2008) Uncovering interactions in the frequency domain. PLoS Comput Biol 4: e1000087+.
13. Spellman PT, Sherlock G, Zhang MQ, Iyer VR, Anders K, et al. (1998) Comprehensive identification of cell cycle-regulated genes of the yeast saccharomyces cerevisiae by microarray hybridization. Mol Biol Cell 9: 3273-3297.
14. Wang RS, Wang Y, Zhang XS, Chen L (2007) Inferring transcriptional regulatory networks from high-throughput data. Bioinformatics.
15. Mewes HW, Frishman D, Güldener U, Mannhaupt G, Mayer K, et al. (2002) Mips: a database for genomes and protein sequences. Nucleic Acids Res 30: 31-34.
16. Teixeira MC, Monteiro P, Jain P, Tenreiro S, Fernandes AR, et al. (2006) The YEASTRACT database: a tool for the analysis of transcription regulatory associations in saccharomyces cerevisiae. Nucleic Acids Res 34.
17. David O, Guillemain I, Saillet S, Reyt S, Deransart C, et al. (2008) Identifying neural drivers with functional mri: An electrophysiological validation. PLoS Biology 6: e315+.
18. Tate AJ, Fischer H, Leigh AE, Kendrick KM (2006) Behavioural and neurophysiological evidence for face identity and face emotion processing in animals. Philos Trans R Soc Lond B Biol Sci 361: 2155-2172.
19. Peirce J, Leigh AE, Kendrick KM (2000) Configurational coding, familiarity and the right hemisphere advantage for face recognition in sheep. Neuropsychologia 38: 475-483.
20. Kosslyn SM, Gazzaniga MS, Galaburda AM, Rabin C (1998) Hemispheric specialization. In: Zigmond MJ, Bloom FE, Landis SC, Roberts JL, Squire LR, eds. Fundamental Neuroscience, Academic Press Inc, chapter 58. pp 1521-1542.
21. Horn RA, Johnson CR (1990) Matrix Analysis. Cambridge University Press.
22. Parkinson H, Kapushesky M, Kolesnikov N, Rustici G, Shojatalab M, et al. (2008) Arrayexpress update-from an archive of functional genomics experiments to the atlas of gene expression. Nucl Acids Res. gkn889+.
23. Barrett T, Troup DB, Wilhite SE, Ledoux P, Rudnev D, et al. (2007) NCBI GEO: mining tens of millions of expression profiles database and tools update. Nucleic Acids Research 35: D760-D765.
24. Fletcher M, Liang B, Smith L, Knowles A, Jackson T, et al. (2008) Neural network based pattern matching and spike detection tools and services - in the CARMEN neuroinformatics project. Neural Networks 21: 1076-1084.
25. Kahvejian A, Quackenbush J, Thompson JF (2008) What would you do if you could sequence everything? Nat Biotech 26: 1125-1133.
26. Shendure J (2008) The beginning of the end for microarrays? Nat Meth 5: 585-587.
27. Friston K (2009) Causal modelling and brain connectivity in functional magnetic resonance imaging. PLoS Biology 7: e33+.
28. Needham CJ, Bradford JR, Bulpitt AJ, Westhead DR (2007) A primer on learning in bayesian networks for computational biology. PLoS Computational Biology 3: e129+.
29. Yu J, Smith AV, Wang PP, Hartemink AJ (2004) Advances to bayesian network inference for generating causal networks from observational biological data. Bioinformatics 20: 3594+.
30. Zou C, Feng J (2009) Granger causality vs. dynamic bayesian network inference: a comparative study. BMC Bioinformatics 10: 122+.
31. Sachs K, Perez O, Pe'er D, Lauffenburger DA, Nolan GP (2005) Causal protein-signaling networks derived from multiparameter single-cell data. Science 308: 523-529.
32. Mukherjee S, Speed TP (2008) Network inference using informative priors. Proceedings of the National Academy of Sciences 105: 14313-14318.
33. Aebersold R, Hood LE, Watts JD (2000) Equipping scientists for the new biology. Nat Biotech 18: 359.
34. Klamt S, Haus UU, Theis F (2009) Hypergraphs and cellular networks. PLoS Comput Biol 5: e1000385+.
35. Royer L, Reimann M, Andreopoulos B, Schroeder M (2008) Unraveling protein networks with power graph analysis. PLoS Comput Biol 4: e1000108+.