Author

Thomas Rohde

University of BonnORCID 0009-0004-5159-4635Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Systems Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:benchmarking· 2 Assay:CRISPR screen· 2 Research Focus:gene regulatory network inference· 2 Approach:machine learning (classical)· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:database / resource· 1

Frequent Co-Authors

Maximilian BillmanniD· 3 shared Amy H.Y. TongiD· 2 shared Angela Helen ShawiD· 2 shared Arshia Zernab HassaniD· 2 shared Barbara MairiD· 2 shared Brenda AndrewsiD· 2 shared Catherine Ross· 2 shared Chad L. MyersiD· 2 shared

Activity by Year

2025-2025 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersBioinformatics

Maximilian BillmannORCID

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Author profile →

3 papers

Recent·Most cited

Quantitative analysis of genetic interactions in human cells from genome-wide CRISPR-Cas9 screens

Maximilian Billmann, Michael Costanzo, Mahfuzur Rahman, Katherine Chan, Amy H.Y. Tong, Henry N. Ward, Arshia Zernab Hassan, Xiang Zhang, Kevin R. Brown, Thomas Rohde, Angela Helen Shaw, Catherine Ross, Jolanda S. van Leeuwen, Michael Aregger, Keith A. Lawson, , Chad L. Myers

The paper develops a method to quantify genetic interactions from CRISPR-Cas9 screens and identifies systematic variations in screen data.

bioRxiv · Jun 30, 2025 · PreprintBioinformatics

A global genetic interaction map of a human cell reveals conserved principles of genetic networks

Maximilian Billmann, Michael Costanzo, Xiang Zhang, Arshia Zernab Hassan, Mahfuzur Rahman, Kevin R. Brown, Katherine Chan, Amy H.Y. Tong, Carles Pons, Henry N. Ward, Catherine Ross, Jolanda S. van Leeuwen, Michael Aregger, Keith A. Lawson, Barbara Mair, , Charles M. Boone

The paper constructs a genome-scale genetic interaction network from 4 million double mutants in HAP1 cells, revealing conserved genetic network principles across species and uncovering novel gene functions and cancer dependencies.

bioRxiv · Jun 30, 2025 · PreprintSystems Biology

BaCoN (Balanced Correlation Network) improves prediction of gene buffering

Thomas Rohde, Talip Yasir Demirtas, Sebastian Süsser, Angela Helen Shaw, Manuel Kaulich, Maximilian Billmann

BaCoN improves gene buffering prediction by enhancing correlation-based networks with CRISPR-Cas9 and transcriptomic data from DepMap cell lines.

Molecular Systems Biology · Apr 22, 2025Peer-reviewedBioinformatics