HAYSTACK utilizes a model-based pattern matching algorithm to identify genes whose expression patterns fit a predefined model.

For example, HAYSTACK has been used to compare microarray time-course data against a collection of diurnal/circadian models to identify cycling genes.

HAYSTACK determines the correlation of an experimental data series with each model pattern and applies a series of statistical tests and ad hoc filters to identify genes of interest and their corresponding best-fitting model.

Project Support - HAYSTACK and the Diurnal Plant Gene Expression Project are supported generously by a Plant Genome Research Program (PGRP) grant from the National Science Foundation (DBI-0605240). The project uses facilities and resources provided by the Department of Botany and Plant Pathology, the Center for Genome Research and Biocomputing, Oregon State University.