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Personal profile

Research Interests

Research in our lab focuses on developing statistical machine learning based algorithms and informatics solutions for knowledge extraction in biology and medicine. Our ongoing research work, funded by National Library of Medicine/NIH R01, focuses on developing novel bioinformatics methods to help in silico discovery and research for accelerating the linkage of phenotypic and genomic information at gene-isoform level. The overarching goal of the lab is to translate data from high dimensional (-omic) platforms (e.g., NextGen sequencing) to derive experimentally interpretable and testable discovery models for the identification and characterization of transcript-variants/protein isoforms, networks and pathways involved in normal and disease cells. Our data science group collaborates with experimental and clinical researchers towards identification of genetic and epigenetic signatures for identification of subsets of cancer patients who may benefit from therapeutic intervention and guide the understanding of drug activity in patient tumors, towards the goals of precision medicine (for example, JCO Clin Cancer Inform. 2019 Apr;3:1-9. doi: 10.1200/CCI.18.00096.)

Data Science; Application of statistical machine learning methods; precision medicine; isoform-level gene regulation

Education/Academic qualification

PhD, Indian Agricultural Statistics Research Institute

… → 1996

Research interests

  • Big Data
  • Bioinformatics
  • Brain Cancer / Nervous System Cancer
  • Cancer Biology
  • Computational Biology
  • Genomics
  • Systems Biology

Fingerprint Dive into the research topics where Ramana V Davuluri is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 24 Similar Profiles
Genes Medicine & Life Sciences
Neoplasms Medicine & Life Sciences
MicroRNAs Medicine & Life Sciences
Genome Medicine & Life Sciences
Gene Expression Medicine & Life Sciences
Glioblastoma Medicine & Life Sciences
Transcription Factors Medicine & Life Sciences
Protein Isoforms Medicine & Life Sciences

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Grants 2012 2023

Informatics
Neoplasms
Medicine
Research
Population
Informatics
Protein Isoforms
Genes
Exons
Chromatin Immunoprecipitation
temozolomide
Glioblastoma
Radiation
Mutation
Neoplasms
Prostatic Neoplasms
Neoplasms
Castration
Research Personnel
EphB4 Receptor

Research Output 1999 2019

2 Citations (Scopus)

IDH3α regulates one-carbon metabolism in glioblastoma

May, J. L., Kouri, F., Hurley, L. A., Liu, J., Tommasini-Ghelfi, S., Ji, Y., Gao, P., Calvert, A. E., Lee, A., Chandel, N., Davuluri, R. V., Horbinski, C. M., Locasale, J. W. & Stegh, A. H., Jan 1 2019, In : Science Advances. 5, 1, eaat0456.

Research output: Contribution to journalArticle

Glioblastoma
Glycine Hydroxymethyltransferase
Carbon
Methionine
Activity Cycles

Platform-independent classification system for predicting high-grade serous ovarian carcinoma molecular subtypes

Shilpi, A., Kandpal, M., Ji, Y., Seagle, BL. & Davuluri, RV., Apr 3 2019, In : JCO Clinical Cancer Informatics. 3, 1, p. 1-9 9 p.

Research output: Contribution to journalArticle

Open Access
RNA Sequence Analysis
Cystic Fibrosis
MicroRNAs
Phenotype
Blood Cells
2 Citations (Scopus)

Characterization of brain tumor initiating cells isolated from an animal model of CNS primitive neuroectodermal tumors

Malchenko, S., Sredni, S. T., Boyineni, J., Bi, Y., Margaryan, N. V., Guda, M. R., Kostenko, Y., Tomita, T., Davuluri, R. V., Velpula, K., Hendrix, M. J. C. & Soares, M. B., Jan 1 2018, In : Oncotarget. 9, 17, p. 13733-13747 15 p.

Research output: Contribution to journalArticle

Primitive Neuroectodermal Tumors
Neoplastic Stem Cells
Brain Neoplasms
Animal Models
Carcinogenesis

Erratum: Publisher Correction: Transcribed ultraconserved region 339 promotes carcinogenesis by modulating tumor suppressor microRNAs (Nature communications (2017) 8 1 (1801))

Vannini, I., Wise, P. M., Challagundla, K. B., Plousiou, M., Raffini, M., Bandini, E., Fanini, F., Paliaga, G., Crawford, M., Ferracin, M., Ivan, C., Fabris, L., Davuluri, R. V., Guo, Z., Cortez, M. A., Zhang, X., Chen, L., Zhang, S., Fernandez-Cymering, C., Han, L. & 14 others, Carloni, S., Salvi, S., Ling, H., Murtadha, M., Neviani, P., Gitlitz, B. J., Laird-Offringa, I. A., Nana-Sinkam, P., Negrini, M., Liang, H., Amadori, D., Cimmino, A., Calin, G. A. & Fabbri, M., Jan 8 2018, In : Nature communications. 9, 1, 1 p.

Research output: Contribution to journalComment/debate

Open Access
document markup languages
suppressors
HTML
MicroRNAs
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