1. Luke Alden Yancy, Jr. Mentor: Robert Riley Broad Institute of MIT & Harvard Cambridge, MA

2. Source: http://staff.vbi.vt.edu/pathport/pathinfo_images/Mycobacterium_tuberculosis/AerosolTransmission.jpghttp://staff.vbi.vt.edu/pathport/pathinfo_images/Mycobacterium_tuberculosis/AerosolTransmission.jpg

3. Source: WHO Stop TB Department, website: www.who.int/tb Deaths Causes by TB (Estimated by WHO) 1998 1,751,858 2006 1,654,805

4.  Learn more about Mycobacterium Tuberculosis (Mtb) using analysis of gene expression data  Biclustering ◦ Bimax (Prelic et al. 2006) ◦ CC (Cheng and Church, 2000) ◦ Plaid Model (Turner et al. 2003) ◦ Spectral (Kluger et al. 2003) ◦ Xmotifs (Murali and Kasif, 2003)  Traditional Clustering ◦ K-Means (MacQueen, 1967) ◦ Hierarchical (Eisen et al. 1998)

6. Traditional ClusteringBiclustering Gene Clusters Based on:All ExperimentsSubsets of Experiments Genes Assigned to Clusters: One-to-One Many-to-Many/ One- to-Many Reproducibility:Yes No (due to random steps in algorithm) Source: Machine Learning and Its Applications to Biology, Tarca et al. 2007. (Editor: Fran Lewitter, Whitehead Institute)

7. Bimax K-Means Boshoff Data (Processed: 3924 Genes, 359 Experiments) Clusters of Genes Source: The Transcriptional Responses of Mycobacterium tuberculosis to Inhibitors of Metabolism. (Boshoff et al. 2004)

8. (Source: http://www.nature.com/nature/journal/v409/n6823/full/4091007a0.html) (proS loci of Mtb ) Cluster Operon Gene Pair (k) (N) (m) (n) Significance of overlap k estimated using hypergeometric distribution:

9. Bimax Biclustering Operon Overlap Source: Prolinks: a database of protein functional linkages derived from coevolution (Bowers et al. 2005)

10.  Random step – lacks reproducibility  No biological soundness  Artificial arrangement of data ◦ Large data sets produce statistically significant, but small clusters  Practicality ◦ Implementation ◦ Large Input Data Sets

11.  K-Means clustering performs better than biclustering on our data set  Next, use motif recognition methods to identify regulatory motifs in clusters  Further development of improved biclustering algorithms

12.  Project Team Robert Riley (Mentor) Brian Weiner  The Broad Institue Eric Lander Core Members SRPG Program Members  Summer Research Program in Genomics (SRPG) Shawna Young Bruce Birren Lucia Vielma Maura Silverstein