Author

Simone Lederer

Radboud University NijmegenORCID 0000-0002-0180-4540Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Assay:ChIP-seq· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1 Approach:statistical model· 1

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Cornelis A. Albers· 1 shared Simon J. van HeeringeniD· 1 shared Tom HeskesiD· 1 shared

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2019-2019 · peak 1/yr

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3 top collaborators · 3 mutual co-author links

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1 shared paperBioinformatics

Cornelis A. Albers

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1 paper

Recent·Most cited

Bayesian Linear Mixed Models for Motif Activity Analysis

Simone Lederer, Tom Heskes, Simon J. van Heeringen, Cornelis A. Albers

The paper compares Bayesian Linear Mixed Models and Ridge Regression for motif activity analysis, finding no performance gain in real data due to similar covariance structures.

bioRxiv · Oct 7, 2019 · PreprintBioinformatics