Author

Chaitra Sarathy

Maastricht UniversityORCID 0000-0003-1115-4323Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Assay:electronic health records· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Assay:metabolomics· 1 Organism:mouse· 1

Frequent Co-Authors

Chris T. EveloiD· 1 shared Homeira Moradi ChamehiD· 1 shared Ilja C.W. ArtsiD· 1 shared Jérémie LefebvreiD· 1 shared Keon ArbabiiD· 1 shared Liang ZhangiD· 1 shared Madeleine R. FalbyiD· 1 shared Mandana Movahed· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperSystems Biology

Chris T. EveloORCID

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2 papers

Recent·Most cited

NeurosciencebioRxivPreprintJun 9, 2025

Hyperpolarization-activated cation channel mediated intrinsic plasticity changes underlie the malleability of with-in cell-type electrophysiological heterogeneity

Homeira Moradi Chameh, Madeleine R. Falby, Yvonne Yang…·Taufik A. Valiante

The paper shows that within-cell-type electrophysiological heterogeneity is malleable and can be restored by blocking HCN currents in epilepsy models.

1 citation

humanmouse

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Systems BiologybioRxivPreprintSep 14, 2020

ComMet: A method for comparing metabolic states in genome-scale metabolic models

Chaitra Sarathy, Marian Breuer, Martina Kutmon…·Ilja C.W. Arts

ComMet is a method for analyzing and comparing metabolic flux states in genome-scale models, identifying distinct network modules and differences in human adipocyte metabolism under varying amino acid uptake conditions.

DOI 10.1101/2020.09.14.296145

humanmetabolomics

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