  The ability of oligonucleotide microarrays to measure gene expression has
been hindered by an imperfect understanding of the relationship between input
RNA concentrations and output signals. We argue that this relationship can be
understood based on the underlying statistical mechanics of these devices. We
present a model that includes the relevant interactions between the molecules.
Our model for the first time accounts for partially zippered probe-target
hybrids in a physically realistic manner, and also includes target-target
binding in solution. Large segments of the target molecules are not bound to
the probes, often in an asymmetric pattern, emphasizing the importance of
modeling zippering properly. The resultant fit between the model and training
data using optimized parameters is excellent, and it also does well at
predicting test data.
