Erin Conlon develops statistical methods for integrating multiple sources of genomic information, including microarray, DNA sequence and functional data. She also develops Bayesian models for genomic data, currently focusing on gene expression meta-analysis. Further research areas involve comparative genomics approaches to identifying genetic regulatory networks in prokaryotic species.
No subject area
A Bayesian Model for Pooling Gene Expression Studies That Incorporates Co-Regulation Information (with Bradley L. L. Postier, Barbara A. Methé, Kelly P. Nevin, and Derek R. Lovley), PLoS ONE (2012)
Current Bayesian microarray models that pool multiple studies assume gene expression is independent of other...
Rapid Changes in Gene Expression Dynamics in Response to Superoxide Reveal SoxRS-Dependent and Independent Transcriptional Networks (with Jeffrey L. Blanchard, Wei-Yun Wholey, and Pablo J. Pomposiello), PLoS ONE (2007)
Background
SoxR and SoxS constitute an intracellular signal response system that rapidly detects changes in...
Bayesian meta-analysis models for microarray data: a comparative study (with Joon J. Song and Anna Liu), BMC Bioinformatics (2007)
Background With the growing abundance of microarray data, statistical methods are increasingly needed to integrate...
Bayesian models for pooling microarray studies with multiple sources of replications (with Joon J. Song and Jun S. Liu), BMC Bioinformatics (2006)
Background Biologists often conduct multiple but different cDNA microarray studies that all target the same...
Program of Gene Transcription for a Single Differentiating Cell Type during Sporulation in Bacillus subtilis (with Patrick Eichenberger, Masaya Fujita, Shane T. Jensen, David Z. Rudner, Stephanie T. Want, Caitlin Ferguson, Koki Haga, Txutomu Sato, Jun S. Liu, and Richard Losick), PLoS Biology (2004)
Asymmetric division during sporulation by Bacillus subtilis generates a mother cell that undergoes a 5-h...