Author

T. Gandhi

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

Signature Assays, Organisms & Methods

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Assay:proteomics· 2 Approach:statistical model· 2 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Research Focus:protein folding & dynamics· 1 Organism:yeast· 1

Frequent Co-Authors

L. Reiter· 2 shared A. Hogrebe· 1 shared A. J. Lawton· 1 shared A. Martinez del Val· 1 shared C. D. Kelstrup· 1 shared D. B. Bekker-Jensen· 1 shared I. Leinert· 1 shared J. Baeza· 1 shared

Activity by Year

2019-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersBiochemistry

L. Reiter

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2 papers

Recent·Most cited

BiochemistrybioRxivFeb 19, 2020

Quantifying dynamic protein acetylation using quantitative stoichiometry

J. Baeza, A. J. Lawton, J. Fan…·J. M. Denu

The paper develops and validates a method to quantify acetylation stoichiometry, revealing dynamic changes in response to serum stimulation across cellular compartments and pathways.

DOI 10.1021/acs.jproteome.0c00088

humanproteomics

𝕏 PostBluesky

BiochemistrybioRxivJun 3, 2019

Rapid and site-specific deep phosphoproteome profiling by data-independent acquisition (DIA) without the need for spectral libraries

D. B. Bekker-Jensen, O. Bernhardt, A. Hogrebe…·J. V. Olsen

This paper introduces a DIA-based phosphoproteomics method that achieves high sensitivity and reproducibility without spectral libraries, demonstrating its scalability in analyzing kinase inhibitor effects on EGF signaling.

DOI 10.1038/s41467-020-14609-1

yeastproteomics

𝕏 PostBluesky