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%\textbf{Compressed Sensing Meets Bioinformatics: A New DNA
%Microarray Architecture} \\
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%\textbf{Olgica Milenkovic$\dag$, Richard Baraniuk$\ddag$, and
%Tajana Simunic-Rosing$\sharp$} \\
%$\dag$   University of Colorado, Boulder, CO\\
%$\ddag$  Rice University, Houston, TX \\
%$\sharp$ University of California, San Diego, CA \\
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DNA Microarrays are one of the most important bioengineering tools
used for comparative gene expression studies and disease
diagnostics. Despite many important advances in microarray
fabrication technology, current state-of-the art array design
principles fail to fully exploit the fact that gene expression
vectors have an inherently sparse structure. This sparse structure
arises due to a variety of biological constraints imposed on the
stability of gene regulatory networks and the complexity of the
network functions.

We describe a new architecture for compressed sensing DNA
microarrays that accounts for genetic data sparsity, and which can
be used in conjunction with efficient all-electronic array readers
and adaptive signal processing systems. The design problem is
approached in terms of combining a myriad of techniques from
bioinformatics, compressed sensing theory, and VLSI design. In
addition, some new and challenging models for DNA compressed
sensing are described, pertaining to non-linear (saturated) data
array sensing and quantization effects.
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