Author

Matthias Barann

Christian-Albrechts-Universität zu KielORCID 0000-0002-6535-0533Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Assay:ChIP-seq· 2 Research Focus:differential expression· 2 Organism:human· 2 Approach:statistical model· 2 Assay:ATAC-seq· 1 Research Focus:benchmarking· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Anupam N. SinhaiD· 2 shared Barbara HutteriD· 2 shared Bärbel Felder· 2 shared Benedikt BrorsiD· 2 shared Fatemeh Behjati ArdakaniiD· 2 shared Gideon Zipprich· 2 shared Gilles GasparoniiD· 2 shared Jörn WalteriD· 2 shared

Activity by Year

2016-2018 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersGenomics

Anupam N. SinhaORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Integrative analysis of single cell expression data reveals distinct regulatory states in bidirectional promoters

Fatemeh Behjati Ardakani, Kathrin Kattler, Karl J. V. Nordström, Nina Gasparoni, Gilles Gasparoni, Sarah Fuchs, Anupam N. Sinha, Matthias Barann, Peter Ebert, Jonas Fischer, Barbara Hutter, Gideon Zipprich, Charles David Imbusch, Bärbel Felder, Jürgen Eils, , Marcel H. Schulz

The paper integrates single cell RNA-seq with bulk epigenomic data to identify distinct regulatory states in bidirectional promoters and their associations with structural features and TF binding.

Epigenetics & Chromatin · Nov 9, 2018Peer-reviewedGenomics

Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction

Florian Schmidt, Nina Gasparoni, Gilles Gasparoni, Kathrin Gianmoena, Cristina Cadenas, Julia K. Polansky, Peter Ebert, Karl J. V. Nordström, Matthias Barann, Anupam N. Sinha, Sebastian Fröhler, Jieyi Xiong, Azim Dehghani Amirabad, Fatemeh Behjati Ardakani, Barbara Hutter, , Marcel H. Schulz

This paper introduces TEPIC, a method that combines open-chromatin data with TF binding affinities to predict gene expression, achieving results comparable to TF ChIP-seq.

Nucleic Acids Research · Oct 24, 2016Peer-reviewedBioinformatics