Markus Ankenbrand
Forschungsgruppenleiter at Julius-Maximilians-Universität Würzburg
Würzburg, Bavaria, Germany
Summary
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Rockstar🎓
Top SchoolMarkus Ankenbrand is a research group leader and computational biologist with 13 years of experience bridging life sciences and software engineering at Julius-Maximilians-Universität Würzburg. He combines a Dr. rer. nat. in life sciences with degrees in biology, computer science and computational mathematics to lead interdisciplinary projects and translate complex sequencing data into actionable results. Markus has a track record of hands-on bioinformatics development—contributing backend code to the widely used MultiQC project, notably implementing parsing, aggregation and visualization for bcl2fastq outputs. His international postdoctoral work includes a short-term project at MIT, reflecting collaborative research at top institutions. Colleagues value his ability to pair rigorous experimental insight with pragmatic software solutions that improve data quality metrics and reporting.
12 years of coding experience
2 years of employment as a software developer
Bachelor, Computational Mathematics, Bachelor, Computational Mathematics at Julius-Maximilians-Universität WürzburgDr. rer. nat., Life Sciences, Dr. rer. nat., Life Sciences at Graduate School of Life Sciences (University of Würzburg)
Stackoverflow
483reputation
26kreached
8answers
0questions
Github Skills (16)
bioinformatics10
json10
python10
data-analysis9
data-visualisation9
data-visualization9
data-visualizations9
reporting-services8
rmarkdown6
knitr6
php6
hash6
oh-my-zsh6
prompt6
r6
Programming languages (21)
Github contributions (5)
MultiQC/MultiQC
Jul 2017 - Jul 2017
Aggregate results from bioinformatics analyses across many samples into a single report.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:44 commits, 4 PRs, 12 comments in 11 days
Contributions summary:Markus primarily contributed to the development of the `bcl2fastq` module within the MultiQC framework. Their work focused on parsing and processing data from bcl2fastq output files, including implementing core functionality for reading and aggregating data from JSON files. The user also added features to generate plots and tables for bcl2fastq data, incorporating specific metrics like yieldQ30 and perfect index reads. They also fixed bugs and improved code readability.
multiqcpythonpypianalysesbioconda
HackyHour/Wuerzburg
Sep 2015 - Jan 2023
Monthly HackyHour meetings in Würzburg
Contributions:1 review, 194 commits, 14 PRs in 7 years 5 months
rubysciencesocial
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