Skip to main content


Improving microarray data analysis

Research Achievements

Improving microarray data analysis

An IGERT student participated in an interdisciplinary team effort to improve the scope and efficiency of microarray data analysis. Specifically, she believes that the copious amounts of data collected from full transcription microarrays is too vast to be analyses manually or by simple clustering tools and that key gene relationships are likely to be missed. Her team created a code that networked several different types of clustering analyses together and looked for correlations across each. Then they applied their analysis to an existing microarray mouse brain database. They found what she is calling "serendipitous discovery" of gene relationships that were missed in previous analyses. She argues that this type of computational methodology could unlock the real power of high throughput microarray data analysis.