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Abhishek S. Dhoble, Ph.D. - Publications

Affiliations: 
2004-2008 Chemical Engineering LIT Nagpur 
 2008-2009 Biological Engineering University of Florida, Gainesville, Gainesville, FL, United States 
 2012-2016 Biological Engineering University of Illinois, Urbana-Champaign, Urbana-Champaign, IL 
 2016-2019 PostDoc NSF/USDA EAGER at UIUC 
 2019-2021 Assistant Professor Chemical Engineering BITS Pilani 
 2021- Assistant Professor Biochemical Engineering Indian Institute of Technology (BHU) 
Area:
Microbiome; Anaerobic Digestion; Flow Cytometry; Machine Learning; Microbial Population Dynamics; Microbiome Characterization
Website:
https://iitbhu.ac.in/dept/bce/people/asdhoblebce
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6 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2023 Priyadarsini M, Kushwaha J, Pandey KP, Rani J, Dhoble AS. Application of flow cytometry for rapid, high-throughput, multiparametric analysis of environmental microbiomes. Journal of Microbiological Methods. 214: 106841. PMID 37832922 DOI: 10.1016/j.mimet.2023.106841  0.427
2019 Dhoble AS, Ryan KT, Lahiri P, Chen M, Pang X, Cardoso FC, Bhalerao KD. Cytometric fingerprinting and machine learning (CFML): A novel label-free, objective method for routine mastitis screening Computers and Electronics in Agriculture. 161: 505-513. DOI: 10.1016/J.Compag.2019.04.029  0.617
2018 Dhoble AS, Lahiri P, Bhalerao KD. Machine learning analysis of microbial flow cytometry data from nanoparticles, antibiotics and carbon sources perturbed anaerobic microbiomes. Journal of Biological Engineering. 12: 19. PMID 30220912 DOI: 10.1186/S13036-018-0112-9  0.665
2018 Dhoble AS, Lahiri P, Bhalerao KD. Machine learning analysis of microbial flow cytometry data from nanoparticles, antibiotics and carbon sources perturbed anaerobic microbiomes Journal of Biological Engineering. 12: 19. DOI: https://doi.org/10.1186/s13036-018-0112-9  0.564
2018 Dhoble AS, Lahiri P, Bhalerao KD. Machine learning analysis of microbial flow cytometry data from nanoparticles, antibiotics and carbon sources perturbed anaerobic microbiomes Journal of Biological Engineering. 12: 19. DOI: 10.1186/s13036-018-0112-9  0.659
2016 Dhoble AS, Bekal S, Dolatowski W, Yanz C, Lambert KN, Bhalerao KD. A novel high-throughput multi-parameter flow cytometry based method for monitoring and rapid characterization of microbiome dynamics in anaerobic systems. Bioresource Technology. 220: 566-571. PMID 27614579 DOI: 10.1016/J.Biortech.2016.08.076  0.622
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