Bhavana Prasher
Scientist-F |
Decision Unit 1: Genomics and Genome Biology
Professor |
Academy of Scientific and Innovative Research
Bhavana Prasher is interested in deciphering genomic and biological basis of the fundamental principles of Ayurveda through their integration with modern scientific methods towards development of integrated medicine and healthcare.
Specific Interests
- Discovery of physiological and molecular markers underlying Prakriti based stratification of health
- Variability in environmental responsiveness at physiological & molecular level among Prakriti groups
- Explore and validate cellular & molecular markers of Dosha & Prakriti using therapeutic interventions of Ayurveda
Her group has been involved in the development of a novel integrative framework for Ayurgenomics research, establishing Prakriti based phenotypic stratification of individuals in diverse ethnic populations and development of a predictive model for prakriti using advanced statistical and machine learning approaches on phenotypic data from two different cohorts. She has also identified genetic markers for hypoxia responsiveness and high altitude adaptation.
Selected Publications
All Citations →- Adhatoda vasica and Tinospora cordifolia extracts ameliorate clinical and molecular markers in mild COVID-19 patients: a randomized open-label three-armed study. Verma M, Rawat N, Rani R, Singh M, Choudhary A, Abbasi S, Kumar M, Kumar S, Tanwar A, Misir BR, Khanna S, Agrawal A, Faruq M, Rai S, Tripathi R, Kumar A, Pujani M, Bhojani M, Pandey AK, Nesari T, Prasher B. Eur J Med Res. 2023 Dec 4;28(1):556.
- Heart rate variability during head-up tilt shows inter-individual differences among healthy individuals of extreme Prakriti types. Rani R, Rengarajan P, Sethi T, Khuntia BK, Kumar A, Punera DS, Singh D, Girase B, Shrivastava A, Juvekar SK, Pesala B, Mukerji M, Deepak KK, Prasher B. Physiol Rep. 2022 Sep;10(17):e15435.
- Whole Exome Sequencing in Healthy Individuals of Extreme Constitution Types Reveals Differential Disease Risk: A Novel Approach towards Predictive Medicine. Abbas T, Chaturvedi G, Prakrithi P, Pathak AK, Kutum R, Dakle P, Narang A, Manchanda V, Patil R, Aggarwal D, Girase B, Srivastava A, Kapoor M, Gupta I, Pandey R, Juvekar S, Dash D, Mukerji M, Prasher B. J Pers Med. 2022 Mar 18;12(3):489.
- Baseline cell proliferation rates and response to UV differ in lymphoblastoid cell lines derived from healthy individuals of extreme constitution types. Chakraborty S, Singhmar S, Singh D, Maulik M, Patil R, Agrawal SK, Mishra A, Ghazi M, Vats A, Natarajan VT, Juvekar S, Prasher B, Mukerji M. Cell Cycle. 2021 May;20(9):903–913.
- Recapitulation of Ayurveda constitution types by machine learning of phenotypic traits. Tiwari P, Kutum R, Sethi T, Shrivastava A, Girase B, Aggarwal S, Patil R, Agarwal D, Gautam P, Agrawal A, Dash D, Ghosh S, Juvekar S, Mukerji M, Prasher B. PLoS One. 2017 Oct 5;12(10):e0185380.