Research in Davuluri lab focuses on developing informatics solutions to solve problems in biology and medicine. Current projects are focused on two closely related areas: (A) mammalian gene regulation at isoform-level, and (B) isoform-level gene regulatory networks in brain development and brain tumors. The overarching goal of his lab is to translate data from high dimensional (-omic) platforms (e.g., NextGen sequencing) to derive experimentally interpretable and testable discovery models towards genomics-based clinical decision support systems for personalized cancer therapy. Towards these goals, his group applies state-of-the-art statistically rigorous data-mining methods and NextGen sequencing based experimental procedures in a systems biology setting. 

His research program is interdisciplinary in nature with a complement of experimental investigation. The current projects of Davuluri laboratory are:

1. Informatics platform for mammalian gene regulation at isoform-level
2. Isoform-level gene regulatory networks in brain development and brain tumors
3. Molecular classification of cancers

Davuluri joined Wistar as an associate professor and director of computational biology in the spring of 2008. Prior to joining Wistar, he was an associate professor (with tenure) and head of the Bioinformatics Consulting Unit in the Human Cancer Genetics Program at Ohio State University’s Comprehensive Cancer Center. Born and raised in India, Davuluri received his bachelor’s degree in mathematics from Nagarjuna University in 1988 and his master’s degree in statistics and computer applications from the Indian Agricultural Statistics Research Institute in 1991. He was awarded a Ph.D. in statistics from the Indian Agricultural Statistics Research Institute in 1996. Davuluri was a postdoctoral fellow in bioinformatics at the University of Ghent, Belgium in 1998, and at Cold Spring Harbor Laboratory from 1999-2001.

Combining his knowledge of computers and biology, Davuluri’s research is technologically driven and interdisciplinary in nature. Coupled with advances in high throughput technologies, his computational modeling work seeks to address key outstanding issues in mammalian development and cancer. Davuluri currently maintains online databases (e.g., MPromDb – Mammalian Promoter Database) and programs for NextGen sequence analysis (e.g., IsoformEx, Isoform level gene expression estimation from RNA-seq data; TPD – Modeling Transcription Factor Binding Site Profiles from ChIP-Seq Data).

1 - Pal, S., Gupta, R. and Davuluri, R.V. (2012) Alternative transcription and alternative splicing in cancer (Invited review, Pharmacology & Therapeutics, In press)

2 - Pal, S., Gupta, R., Kim, H., Wickramasinghe, P., Baubet, V., Showe, L.C., Dahmane, N. and Davuluri, R.V. (2011) Alternative transcription exceeds alternative splicing in generating the transcriptome diversity of cerebellar development, Genome Research, 21(8): 1260-1272. 21712398

3 - Bi, Y., Kim, H., Gupta, R. and Davuluri, R.V. (2011) Tree-based Position Weight Matrix Approach to Model Transcription Factor Binding Site Profiles, PLOS One 6(9): e24210. doi:10.1371/journal.pone.0024210. 21912677

4 - Kim, H., Bi, Y., Pal, S., Gupta, R., and Davuluri, R.V. (2011) IsoformEx: Isoform level expression estimation using weighted non-negetive least squares from mRNA-seq data, BMC Bioinformatics, 12(1):305. 21794104

5 - Sun, H., Wu, J., Wickramasinghe, P., Pal, S., Gupta, R., Bhattacharyya, A., Agosto-Perez, F.J., Showe, L.C., Huang, T.H. and Davuluri, R.V. (2011) Genome-wide mapping of RNA Pol-II promoter usage in mouse tissues by ChIP-seq, Nucleic Acids Res, 39, 190-201. 20843783

6 - Gupta, R., Bhattacharyya, A., Agosto-Perez, F.J., Wickramasinghe, P. and Davuluri, R.V. (2011) MPromDb update 2010: an integrated resource for annotation and visualization of mammalian gene promoters and ChIP-seq experimental data, Nucleic Acids Res, 39, D92-97. 21097880

7 - Nicoloso, M.S., Sun, H., Spizzo, R., Kim, H., Wickramasinghe, P., Shimizu, M., Wojcik, S.E., Ferdin, J., Kunej, T., Xiao, L., Manoukian, S., Secreto, G., Ravagnani, F., Wang, X., Radice, P., Croce, C.M., Davuluri, R.V.* and Calin, G.A.* (2010) Single-Nucleotide Polymorphisms Inside MicroRNA Target Sites Influence Tumor Susceptibility, Cancer Res. (*Joint corresponding authors) 20332227

8 - Gupta, R., Wikramasinghe, P., Bhattacharyya, A., Perez, F.A., Pal, S. and Davuluri, R.V. (2010) Annotation of gene promoters by integrative data-mining of ChIP-seq Pol-II enrichment data, BMC Bioinformatics, 11 Suppl 1, S65. 20122241

9 - Qin, H., Chan, M.W., Liyanarachchi, S., Balch, C., Potter, D., Souriraj, I.J., Cheng, A.S., Agosto-Perez, F.J., Nikonova, E.V., Yan, P.S., Lin, H.J., Nephew, K.P., Saltz, J.H., Showe, L.C., Huang, T.H. and Davuluri, R.V. (2009) An integrative ChIP-chip and gene expression profiling to model SMAD regulatory modules, BMC Syst Biol, 3, 73. 19615063

10 - Davuluri, R.V., Suzuki, Y., Sugano, S., Plass, C. and Huang, T.H. (2008) The functional consequences of alternative promoter use in mammalian genomes, Trends Genet, 24, 167-177. 18329129

11 - Davuluri R.V., Grosse, I. and Zhang, M.Q. (2001). Computational identification of first exons and promoters in the human genome. Nature Genetics, 29: 412-417. (Note: This work was featured in Nature Reviews Genetics, 3: 3-9; in Bioinformatics section of Highlights as “Filling the gap in gene prediction” January, 2002). 11726928