Author

Karsten Zengler

Primary ORCID profile (0000-0002-8062-3296 · 18 papers)Unclaimed ORCID profile · follow to get notified of new preprints

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Same name, identified by ORCID

Karsten ZengleriD18 papers · University of California San Diego

Biology Disciplines

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Bioengineering· 1 Bioinformatics· 1 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Approach:experimental assay· 2 Research Focus:benchmarking· 1 Assay:ChIP-seq· 1 Organism:E. coli· 1 Research Focus:gene regulatory network inference· 1 Research Focus:genome assembly· 1 Assay:proteomics· 1

Frequent Co-Authors

Ali Ebrahim· 1 shared Amelie SteiniD· 1 shared Bernhard Palsson· 1 shared Hamidreza Chitsaz· 1 shared Harish Nagarajan· 1 shared Haythem Latif· 1 shared Jakob R. WintheriD· 1 shared Janna Tarasova· 1 shared

Activity by Year

2014-2018 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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1 shared paperMolecular Biology

Ali Ebrahim

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Author profile →

3 papers

Recent·Most cited

ChIP-exo interrogation of Crp, DNA, and RNAP holoenzyme interactions

Haythem Latif, Stephen Federowicz, Ali Ebrahim, Janna Tarasova, Richard Szubin, Jose Utrilla, Karsten Zengler, Bernhard Palsson

This study uses ChIP-exo to analyze Crp, DNA, and RNAP holoenzyme interactions, finding Crp does not protect the DNA motif but shows binding patterns similar to σ70, suggesting it dissociates post-recruitment during transcription initiation.

PLOS ONE · May 17, 2018Peer-reviewedMolecular Biology

Deep mutational scanning by FACS-sorting of encapsulated E. coli micro-colonies

Lars Behrendt, Amelie Stein, Shiraz Ali Shah, Karsten Zengler, Søren J. Sørensen, Kresten Lindorff-Larsen, Jakob R. Winther

This paper introduces a method for high-throughput screening of protein variants using encapsulated E. coli micro-colonies and evaluates biophysical predictors for mutation effects on GFP fluorescence.

bioRxiv · Mar 2, 2018 · PreprintBioengineering

Efficient synergistic single-cell genome assembly

Narjes S. Movahedi, Zeinab Taghavi, Mallory Embree, Harish Nagarajan, Karsten Zengler, Hamidreza Chitsaz

This paper introduces HyDA, a co-assembly algorithm that improves single-cell genome assembly quality by combining multiple datasets, resulting in longer contigs and more complete genomes.

bioRxiv · Feb 24, 2014Bioinformatics