Author

Christoph Kämpf

Helmholtz Centre for Environmental ResearchORCID 0000-0002-3470-6779Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:bulk RNA-seq· 2 Assay:ATAC-seq· 1 Research Focus:deconvolution· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Organism:human· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Alexander ScholziD· 2 shared Kristin ReicheiD· 2 shared Aaron M. NewmaniD· 1 shared Aashi Jain· 1 shared Alberto ValdeolivasiD· 1 shared Andrew E. LambiD· 1 shared Andrew J. GentlesiD· 1 shared Aurélien de ReynièsiD· 1 shared

Activity by Year

2019-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Alexander ScholzORCID

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2 papers

Recent·Most cited

Community assessment of methods to deconvolve cellular composition from bulk gene expression

Brian S. White, Aurélien de Reyniès, Aaron M. Newman, Joshua J. Waterfall, Andrew E. Lamb, Florent Petitprez, Yating Lin, Rongshan Yu, Martin E. Guerrero-Gimenez, Sergii Domanskyi, Gianni Monaco, Verena Chung, Jineta Banerjee, Daniel S. Derrick, Alberto Valdeolivas, , Andrew J. Gentles

The paper evaluates deconvolution methods for inferring immune infiltration from bulk gene expression using a DREAM Challenge, finding that some community-contributed methods, especially deep learning-based ones, perform well.

Nature Communications · Aug 27, 2024Peer-reviewedBioinformatics

uap: Reproducible and Robust HTS Data Analysis

Christoph Kämpf, Michael Specht, Alexander Scholz, Sven-Holger Puppel, Gero Doose, Kristin Reiche, Jana Schor, Jörg Hackermüller A

The paper introduces uap, a workflow management system for reproducible and robust HTS data analysis, addressing reproducibility challenges in complex bioinformatic pipelines.

BMC Bioinformatics · Dec 1, 2019Peer-reviewedBioinformatics