Author

A. Ghatak

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biochemistry· 2 Bioengineering· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 2 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Organism:E. coli· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Assay:metabolomics· 1

Frequent Co-Authors

S. Datta· 4 shared A. P. Shanbhag· 3 shared N. Katagihallimath· 2 shared S. Rajagopal· 2 shared D. G. Madival· 1 shared D. Kundu· 1 shared D. Mookherjee· 1 shared G. Tomar· 1 shared

Activity by Year

2019-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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4 shared papersBiochemistry

S. Datta

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Reducing the vicissitudes of heterologous prochiral substrate catalysis by alcohol dehydrogenases through machine learning algorithms

A. Ghatak, A. P. Shanbhag, S. Datta

This study uses machine learning to classify substrates for alcohol dehydrogenase superfamilies, reducing the need for high-throughput screening.

bioRxiv · Sep 26, 2023Biochemistry

ZeBox: A novel non-intrusivecontinuous-use technology to trap and killairborne microbes

K. S. Phadke, D. G. Madival, J. Venkatraman, D. Kundu, K. S. Ramanujan, N. Holla, J. Arakeri, G. Tomar, S. Datta, A. Ghatak

ZeBox is a new air decontamination technology that uses an electric field and engineered surfaces to trap and kill airborne microbes efficiently and safely.

bioRxiv · Aug 2, 2021Microbiology

Flexibility of Short-chain dehydrogenase is interconnected to its promiscuity for the reduction of multiple ketone intermediates

A. P. Shanbhag, S. Rajagopal, A. Ghatak, N. Katagihallimath, R. S., S. Datta

The paper uses machine learning to identify promiscuous SDRs based on physicochemical properties, showing a correlation between C-terminal structure, melting temperature, and catalytic efficiency.

bioRxiv · Jul 5, 2021Biochemistry

Maximization of non-nitrogenous metabolite production in E. coli using population systems biology

S. Rajagopal, A. Ghatak, D. Mookherjee, R. V. Hmar, A. P. Shanbhag, J. Venkataraman, N. Katagihallimath, R. K. S, S. Datta

This paper develops a population systems biology algorithm to enhance non-nitrogenous metabolite production in E. coli by considering transcriptome diversity and introducing nitrogen-swap strategies.

bioRxiv · Dec 27, 2019Bioengineering