Author

Uwe Schmitt

ETH ZurichORCID 0000-0002-4658-0616Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:variant calling· 2 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Organism:human· 1 Assay:metabolomics· 1 Assay:proteomics· 1

Frequent Co-Authors

Aashil A. BataviaiD· 1 shared Alessandro Ori‬‬iD· 1 shared Anika JohniD· 1 shared Arthur DondiiD· 1 shared Augustin LunaiD· 1 shared Benjamin Langer· 1 shared Chaoran CheniD· 1 shared Ching Chiek KohiD· 1 shared

Activity by Year

2019-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperBioinformatics

Aashil A. BataviaORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

V-pipe 3.0: a sustainable pipeline for within-sample viral genetic diversity estimation

Lara Fuhrmann, Kim Philipp Jablonski, Ivan Topolsky, Aashil A. Batavia, Nico Borgsmüller, Pelin Icer Baykal, Matteo Carrara, Chaoran Chen, Arthur Dondi, Monica Dragan, David Dreifuss, Anika John, Benjamin Langer, Michal J. Okoniewski, Louis du Plessis, , Niko Beerenwinkel

V-pipe 3.0 is a computational pipeline for analyzing viral genomic data, enabling reproducible and scalable estimation of within-sample genetic diversity.

GigaScience · Jan 1, 2024Peer-reviewedBioinformatics

ScalaFlux: a scalable approach to quantify fluxes in metabolic subnetworks

Pierre Millard, Uwe Schmitt, Patrick Kiefer, Julia A. Vorholt, Stéphanie Heux, Jean‐Charles Portais

ScalaFlux quantifies metabolic fluxes in subnetworks without requiring external network information, validated on yeast mutants and simulated data.

PLoS Computational Biology · Apr 14, 2020Peer-reviewedSystems Biology

Rapid proteotyping reveals cancer biology and drug response determinants in the NCI-60 cells

Tiannan Guo, Augustin Luna, Vinodh N. Rajapakse, Ching Chiek Koh, Zhicheng Wu, Michael P. Menden, Yongran Cheng, Laurence Calzone, Loredana Martignetti, Alessandro Ori‬‬, Murat Iskar, Ludovic C. J. Gillet, Qing Zhong, Sudhir Varma, Uwe Schmitt, , Ruedi H. Aebersold

This study rapidly generates proteomic data for NCI-60 cancer cell lines and identifies drug response determinants by integrating proteomic, genetic, and transcriptomic data.

bioRxiv · Mar 7, 2019 · PreprintSystems Biology