Author

Georg Stricker

Technical University of MunichORCID 0000-0003-2949-1758Unclaimed 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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Assay:ChIP-seq· 2 Approach:statistical model· 2 Research Focus:differential expression· 1 Organism:human· 1 Research Focus:variant effect prediction· 1 Organism:yeast· 1

Frequent Co-Authors

Julien GagneuriD· 2 shared Achim TreschiD· 1 shared Alexander Engelhardt· 1 shared Daniel SchulziD· 1 shared Mathilde Galinier· 1 shared Matthias C. SchmidiD· 1 shared

Activity by Year

2017-2018 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 11 mutual co-author links

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2 shared papersBioinformatics

Julien GagneurORCID

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2 papers

Recent·Most cited

BioinformaticsBMC BioinformaticsPeer-reviewedJun 26, 2018

GenoGAM 2.0: Scalable and efficient implementation of genome-wide generalized additive models for gigabase-scale genomes

Georg Stricker, Mathilde Galinier, Julien Gagneur

GenoGAM 2.0 improves the speed and scalability of genome-wide generalized additive models for ChIP-Seq data analysis, enabling efficient processing of large genomes.

2 citations

humanChIP-seq

𝕏 PostBluesky

BioinformaticsBioinformaticsPeer-reviewedMar 20, 2017

GenoGAM: Genome-wide generalized additivemodels for ChIP-seq analysis

Georg Stricker, Alexander Engelhardt, Daniel Schulz…·Julien Gagneur

GenoGAM improves ChIP-seq differential occupancy analysis by using generalized additive models to avoid subjective binning, increasing sensitivity while controlling type I error.

7 citations

yeastChIP-seq

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