Author

Nina Gasparoni

Saarland University

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· 2 Genomics· 2

Signature Assays, Organisms & Methods

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Assay:ChIP-seq· 4 Research Focus:differential expression· 3 Research Focus:gene regulatory network inference· 3 Organism:human· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Assay:DNA methylation· 2 Assay:ATAC-seq· 1

Frequent Co-Authors

Jörn WalteriD· 4 shared Gilles GasparoniiD· 3 shared Karl J. V. NordströmiD· 3 shared Marcel H. SchulziD· 3 shared Peter EbertiD· 3 shared Thomas LengaueriD· 3 shared Anupam N. SinhaiD· 2 shared Barbara HutteriD· 2 shared

Activity by Year

2016-2019 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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4 shared papersBioinformatics

Jörn WalterORCID

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Author profile →

4 papers

Recent·Most cited

CRUP: A comprehensive framework to predict condition-specific regulatory units

Anna Ramisch, Verena Heinrich, Laura V. Glaser, Alisa Fuchs, Xinyi Yang, Philipp Benner, Robert Schöpflin, Na Li, Sarah Kinkley, Anja Römer-Hillmann, John Longinotto, Steffen Heyne, Beate Czepukojc, Sonja M. Kessler, Alexandra K. Kiemer, , Martin Vingron

CRUP predicts condition-specific regulatory units by analyzing histone modification ChIP-seq data and linking enhancers to target genes in rheumatoid arthritis.

Genome biology · Nov 7, 2019Peer-reviewedBioinformatics

Unique and assay specific features of NOMe-, ATAC- and DNase I-seq data

Karl J. V. Nordström, Florian Schmidt, Nina Gasparoni, Abdulrahman Salhab, Gilles Gasparoni, Kathrin Kattler, Fabian Müller, Peter Ebert, Ivan G. Costa, Nico Pfeifer, Thomas Lengauer, Marcel H. Schulz, Jörn Walter

The paper compares DNase I-Seq, ATAC-Seq, and NOMe-Seq to identify assay-specific features and their impact on chromatin accessibility and gene expression prediction.

Nucleic Acids Research · Sep 11, 2019Peer-reviewedGenomics

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