Author

Cornelis A. Albers

Radboud University Nijmegen

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1 Genetics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:Bayesian inference· 2 Assay:DNA methylation· 2 Research Focus:gene regulatory network inference· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:ChIP-seq· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

Alejandro Arias-Vasquez· 1 shared Barbara FrankeiD· 1 shared Hendrik G. StunnenbergiD· 1 shared Hilbert J. Kappen· 1 shared Jan P. GerlachiD· 1 shared Jesse Middelwijk· 1 shared Jessie A.G.L. van BuggenumiD· 1 shared Jonathan MarchiniiD· 1 shared

Activity by Year

2016-2019 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperGenetics

Alejandro Arias-Vasquez

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3 papers

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

Immuno-Detection by sequencing (ID-seq) enables large-scale high-dimensional phenotyping in cells.

Jessie A.G.L. van Buggenum, Jan P. Gerlach, Sabine E.J. Tanis, Mark Hogeweg, Pascal W.T.C. Jansen, Jesse Middelwijk, Ruud van der Steen, Michiel Vermeulen, Hendrik G. Stunnenberg, Cornelis A. Albers, Klaas W. Mulder

The paper introduces ID-seq, a technology that measures multiple molecular and cellular phenotypes in parallel, and uses it to study kinase inhibitor effects on human epidermal stem cells.

Nature Communications · Jun 13, 2018Peer-reviewedGenomics

Explaining Missing Heritability Using Gaussian Process Regression

Kevin Sharp, Wim Wiegerinck, Alejandro Arias-Vasquez, Barbara Franke, Jonathan Marchini, Cornelis A. Albers, Hilbert J. Kappen

This paper uses Gaussian Process Regression to explain missing heritability in yeast and rat phenotypes, finding that non-additive interactions account for most of the missing heritability.

bioRxiv · Feb 22, 2016 · PreprintGenetics