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Received October 2003; revised June 2004; accepted August 2004 ACM Transactions on Information Systems, Vol. 23, No. 1, January 2005. A Methodology for Analyzing SAGE Libraries for Cancer Profiling ¨ JORG SANDER University of Alberta RAYMOND T. NG, MONICA C. SLEUMER, and MAN SAINT YUEN University of British Columbia and STEVEN J. JONES British Columbia Genome Sciences Centre Serial Analysis of Gene Expression (SAGE) has proven to be an important alternative to microarray techniques for global profiling of mRNA populations.

One of the most significant applications could be its use for large public databases, such as NCBI, that make thousands of genomes available for everyone over the Internet. This compression algorithm could already help cut transmission costs. Furthermore, decoding has very low resource requirements, making its use possible in many environments. ACKNOWLEDGMENTS The authors gratefully acknowledge the useful suggestions and comments of Professor Jorma Rissanen on an early version of the manuscript.

Dev. 20, 3, 198–203. , AND DELGRANGE, O. 1995. A guaranteed compression scheme for repetitive DNA sequences. Tech. Rep. IT–285, LIFL Lille I Univ. , AND RISSANEN, J. 2003a. DNA sequence compression using the normalized maximum likelihood model for discrete regression. In Proceedings of the Data Compression Conference. 253–262. , AND ASTOLA, J. 2003b. Classification and feature gene selection using the normalized maximum likelihood model for discrete regression. Signal Processing, Special Issue on Genomic Signal Processing 83, 4 (April), 713–727.

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ACM transactions on information systems (January) by Association for Computing Machinery


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