Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Biological or biochemical
Reexamination Certificate
2002-09-26
2008-09-30
Clow, Lori A (Department: 1631)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Biological or biochemical
C702S020000, C435S006120
Reexamination Certificate
active
07430475
ABSTRACT:
Embodiments of this invention include application of new inferential methods to analysis of complex biological information, including gene networks. In some embodiments, disruptant data and/or drug induction/inhibition data are obtained simultaneously for a number of genes in an organism. New methods include modifications of Boolean inferential methods and application of those methods to determining relationships between expressed genes in organisms. Additional new methods include modifications of Bayesian inferential methods and application of those methods to determining cause and effect relationships between expressed genes, and in some embodiments, for determining upstream effectors of regulated genes. Additional modifications of Bayesian methods include use of heterogeneous variance and different curve fitting methods, including spline functions, to improve estimation of graphs of networks of expressed genes. Other embodiments include the use of bootstrapping methods and determination of edge effects to more accurately provide network information between expressed genes. Methods of this invention were validated using information obtained from prior studies, as well as from newly carried out studies of gene expression.
REFERENCES:
Pe'er et al. (Bioinfomatics (2001) vol. 17, Suppl. 1, pp. S215-S224).
Ideker, et al., Integrated Genomic and Proteoic Analyses of a Systematically Perturbed Metabolic Newtork. Science. May 4, 2001, vol. 292, pp. 929-934.
Friedman, et al.., Using Bayesian Networks to Analyze Expression Data. J. Computational Biology. 2000, vol. 7, Nos. 3/4, pp. 601-620.
Pe'er, et al., “Inferring subnetworks from perturbed expression profiles”, In: School of Computer Science and Engineering (Hegrew University, Jerusalm). Oxford University Press. Jun. 2001, vol. 17, Suppl. 1, pp. S214-S224.
Imoto, et al. Bayesian network and nonparametric heteroscedastic regression for nonlinear modeling of genetic network. Proc IEEE Comput Soc Bioinform Conf. 2002; 1:219-27.
Imoto, et al. Estimation of genetic networks and functional structures between genes by using Bayesian networks and nonparametric regression. Pac Symp Biocomput. 2002; 175-86.
de Hoon Michiel
Goto Takao
Imoto Seiyo
Kuhara Saturo
Miyano Satoru
Clow Lori A
GNI KK
Wilson Sonsini Goodrich & Rosati
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