Photo of Rahul Kulkarni,  PhD

Rahul Kulkarni, PhD

University Of Massachusetts - Boston

University Of Massachusetts - Boston
Phone: (617) 287-6272


rahul.kulkarni@umb.edu

Rahul Kulkarni, PhD

University Of Massachusetts - Boston

EDUCATIONAL TITLES

  • Associate Professor, College of Science and Math, University Of Massachusetts - Boston
  • Associate Professor, Physics, University Of Massachusetts - Boston

DF/HCC PROGRAM AFFILIATION

Research Abstract

My background and training is in physics and my thesis research involved analysis of disordered systems using statistical mechanics and computational modeling. As a postdoctoral researcher, I started to use these approaches to analyze biological processes and networks. Using bioinformatic approaches, I made theoretical predictions for small RNAs in the quorum-sensing pathways in the Vibrios which were validated by our experimental collaborators. This project was a wonderful interdisciplinary research experience which taught me how the successful integration of bioinformatics, computational modeling and experimental molecular biology can lead to novel discoveries and high-impact research.

My current research focuses on stochastic modeling of gene expression and its regulation by non-coding RNAs. I have mentored postdoctoral researchers, graduate students and undergraduate students in these topics. All my group members have been well-placed after leaving the group, securing postdoctoral positions in Universities such as Stanford and Duke, and faculty positions in England and India. The undergraduate students I have mentored have received multiple awards related to their research including the Barry M. Goldwater Fellowship and have gone on to graduate school at Universities such as UC Davis and Harvard.

My current research focuses on the application of bioinformatic and modeling approaches to projects involving the role of non-coding RNAs in cancer. Specifically, I am collaborating with the groups of Dr. Pier Paolo Pandolfi (DF/HCC) and Prof. Kourosh Zarringhalam (UMass Boston) towards the discovery and analysis of non-coding ceRNA regulators of the tumor suppressor gene PTEN. We have currently made predictions for long non-coding RNAs which can potentially function as ceRNAs of PTEN which are being validated in the Pandolfi lab. The application and extension the approaches developed by my group to modeling post-transcriptional regulatory networks in cancer presents an exciting opportunity. In summary, I believe that my previous research efforts, in combination with current collaboration with experimental groups at DF/HCC, have the potential to lead to significant new discoveries in current research focusing on the role of non-coding RNAs and stochastic gene expression in cancer.

Publications

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  • Kumar N, Platini T, Kulkarni RV. Exact distributions for stochastic gene expression models with bursting and feedback. Phys Rev Lett 2015; 113:268105. PubMed
  • Kulkarni PR, Jia T, Kuehne SA, Kerkering TM, Morris ER, Searle MS, Heeb S, Rao J, Kulkarni RV. A sequence-based approach for prediction of CsrA/RsmA targets in bacteria with experimental validation in Pseudomonas aeruginosa. Nucleic Acids Res 2014. PubMed
  • Kulkarni RV. Queueing up for translation. Biophys J 2013; 104:2329-30. PubMed
  • Pendar H, Platini T, Kulkarni RV. Exact protein distributions for stochastic models of gene expression using partitioning of Poisson processes. Phys Rev E Stat Nonlin Soft Matter Phys 2013; 87:042720. PubMed
  • Kulkarni P, Shiraishi T, Kulkarni RV. Cancer: tilting at windmills? Mol Cancer 2013; 12:108. PubMed
  • Baker C, Jia T, Kulkarni RV. Stochastic modeling of regulation of gene expression by multiple small RNAs. Phys Rev E Stat Nonlin Soft Matter Phys 2012; 85:061915. PubMed
  • Platini T, Jia T, Kulkarni RV. Regulation by small RNAs via coupled degradation: mean-field and variational approaches. Phys Rev E Stat Nonlin Soft Matter Phys 2011; 84:021928. PubMed
  • Elgart V, Jia T, Fenley AT, Kulkarni R. Connecting protein and mRNA burst distributions for stochastic models of gene expression. Phys Biol 2011; 8:046001. PubMed
  • Jia T, Kulkarni RV. Intrinsic noise in stochastic models of gene expression with molecular memory and bursting. Phys Rev Lett 2011; 106:058102. PubMed
  • Elgart V, Jia T, Kulkarni RV. Applications of Little's Law to stochastic models of gene expression. Phys Rev E Stat Nonlin Soft Matter Phys 2010; 82:021901. PubMed
  • Jia T, Kulkarni RV. Post-transcriptional regulation of noise in protein distributions during gene expression. Phys Rev Lett 2010; 105:018101. PubMed
  • Elgart V, Jia T, Kulkarni R. Quantifying mRNA synthesis and decay rates using small RNAs. Biophys J 2010; 98:2780-4. PubMed
  • Tsou AM, Cai T, Liu Z, Zhu J, Kulkarni RV. Regulatory targets of quorum sensing in Vibrio cholerae: evidence for two distinct HapR-binding motifs. Nucleic Acids Res 2009; 37:2747-56. PubMed
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