DIMACS Workshop on Analysis of Gene Expression Data

October 24 - 26, 2001
DIMACS Center, Rutgers University, Piscataway, NJ

Laurie Heyer, Davidson College, laheyer@davidson.edu
Gustavo Stolovitzky, IBM, gustavo@us.ibm.com
Shibu Yooseph, Celera Genomics, shibu.yooseph@celera.com
Presented under the auspices of the Special Year on Computational Molecular Biology.

The gene expression array is a significant new technology aimed at providing a top down picture of the intimate genetic processes of an organism.

Whether an array is implemented using photolithography and silicon-based fabrication, capillary printing heads on a glass slide, or ink-jet technology, it allows quantification of transcription levels of large numbers of genes simultaneously.

Few years have passed since the first microarray-based biological results were published and it already seems unthinkable to tackle the complexities of the workings of the cell without these devices. However there remain unsolved image processing as well as computational and mathematical difficulties associated with the extraction and validation of data from gene expression microarray assays.

In the image processing domain, active research areas include noise estimation, background subtraction, and quality assessment in the feature recognition process. Downstream of the image analysis lays the problems of reconstruction of biochemical pathways and genetic networks from transcriptional data. Subproblems include clustering transcription profiles of multiple genes over time and/or over populations, graph problems such as constructing metabolic pathways consistent with gene transcription clusters, string problems such as finding promoter sequences in genomic sequence that explain co-regulation, and probabilistic problems such as assessing the statistical significance of transcriptional patterns.

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Document last modified on March 29, 2000.