Data processing: database and file management or data structures – Database and file access – Preparing data for information retrieval
Reexamination Certificate
2006-07-31
2010-12-07
Truong, Cam Y (Department: 2169)
Data processing: database and file management or data structures
Database and file access
Preparing data for information retrieval
C707S705000, C707S736000
Reexamination Certificate
active
07849088
ABSTRACT:
Gene expression, or other data is analyzed for the presence of biclusters. The data is represented as geometric data. Lines, planes and/or hyperplanes are detected in the geometric data using a transform such as a Hough Transform or its variations. The detected lines, planes and hyperplanes are analyzed to determine if they correspond to biclusters in the original data.
REFERENCES:
patent: 6289354 (2001-09-01), Aggarwal et al.
patent: 7035739 (2006-04-01), Schadt et al.
patent: 7075547 (2006-07-01), Moon
patent: 7406212 (2008-07-01), Mohamed et al.
patent: 7567972 (2009-07-01), Geiselhart et al.
patent: 2005/0278324 (2005-12-01), Fan et al.
patent: 2006/0184459 (2006-08-01), Parida
patent: 2008/0021897 (2008-01-01), Lepre
Madeira, S.C. and Oliveira, A. L., “Biclustering algorithms for biological data analysis: A survey,” IEEE Transactions on Computational Biology Bioinformatics, Jan.-Mar. 2004, vol. 1, pp. 24-45.
Li, H., Lavin, M. A., and Le Master, R. J., “Fast Hough Transform: A Hierarchical Approach,” Computer Vision, Graphics, and Image Processing, 1986, vol. 36, pp. 139-161.
Li, H., Lavin, M.A., and Le master, R. J., “Fast Hough Transform: A hierarchical Approach,” Computer Vision, Graphics, and Image Processing, 1986, vol. 36, pp. 139-161.
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopolos, Prabhakar Raghavan, “Automatic Subspace Clustering of High Demensional Data for Data Mining Applications”, IBM Almaken Research Center, 650 Harry Rioad, San Jose, CA 95120, vol. 27, Issue 2 (Jun. 1998).
Tavazoie, S., et al., “Systematic determination of genetic network architecture,” Nature Genetics, vol. 22, 1999, pp. 281-285.
Eisen, M.B., et al., “Cluster analysis and display of genome-wide expression patterns,” Proc. Natl. Acad. Sci. USA, 1998, vol. 95, pp. 14863-14868.
Tamayo, P., et al., “Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation,” Proc. Natl. Acad. Sci. USA, 1999, vol. 96, pp. 2907-2912.
Segal, E., et al., “Rich probabilistic models for gene expression,” Bioinformatics, vol. 17, 2001, pp. 243-252.
Kluger, Y., Basri, R., Chang, J. T., and Gerstein, M., “Spectral Biclustering of Microarray Data: Coclustering Genes and Samples,” Genome Research, Cold Spring Harbor Laboratory Press ISSN 1088-9051/03, 2003, vol. 13, 703-716.
Li, H., Lavin, M. A., and Le Master, R. J., “Fast Hough Transform: A Hierarchical Approach,” Computer Vision, Graphics, and Image Processing, 1986, vol. 36, pp. 139-161.
Kiryati, N., Eldar,Y., and Bruckstein, A.M., “A Probabilistic Hough Transform,” Pattern Recognition, 1990, vol. 24, pp. 303-316.
Xu, L. and Oja, E., “Rnadomized Hough Transform (RHT): Basic Mechanisms, Algorithms, and Computational Complexities,” CVGIP: Image Understanding, vol. 57, No. 2, Mar. 1993, pp. 131-154.
Gan, X., Liew, A. W. C., and Yan, H, “Microarray missing data imputation based on a set theoretic framework and biological knowledge,” Nucleic Acids Research, 2006, vol. 34, No. 5, pp. 1608-1619.
Tanay, A., Sharan, R. and Shamir, R., “Discovering statistically significant biclusters in gene expression data,” Bioinformatics, vol. 18, Suppl. 1, 2002, pp. S136-S144.
Delong, M., et al., “DIG—a system for gene annotation and functional discovery,” Bioinformatics, vol. 21, No. 13, 2005, pp. 2957-2959.
Ashburner, M., et al., “Gene Ontology: tool for the unification of biology,” The Gene Ontology Consortium, Nature Genetics, 2000, vol. 25, pp. 25-29.
Gan Xiangchao
Liew Alan Wee-Chung
Yan Hong
City University of Hong Kong
Heslin Rothenberg Farley & & Mesiti P.C.
Truong Cam Y
Vo Cecile
LandOfFree
Representation and extraction of biclusters from data arrays does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Representation and extraction of biclusters from data arrays, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Representation and extraction of biclusters from data arrays will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-4178896