Michał Lorenc is a Bioinformatics Specialist with nearly two decades of experience and 11 years of focused professional work building scalable, reproducible pipelines for large and complex genomic datasets. He combines deep bioinformatics domain expertise—leading chromosome-level assemblies, pangenome construction, comparative genomics and ChIP/ RNA-seq analyses—with strong software engineering practices like parallel processing, polyglot persistence and containerized reproducibility (Docker/Singularity). At QUT he contributed to high-profile publications (including Nature Plants), built custom hybrid assembly and Hi-C workflows, and automated packaging for Bioconda to streamline tool distribution. Comfortable across Python, HPC and cloud environments, he also mentors PhD students and translates validation requirements into robust testing and deployment practices. He is distinctive for turning production-scale biological bottlenecks into engineered solutions, often by writing custom wrappers that partition and distribute data across cores or nodes.
11 years of coding experience
10 years of employment as a software developer
Master of Science (M.Sc.), Bioinformatics, Master of Science (M.Sc.), Bioinformatics at Center for Bioinformatics of the University Hamburg (Germany)
Bioinformatics - Structural Chemistry, Bioinformatics - Structural Chemistry at Eskitis Institute
Bachelor of Science (B.Sc.), Information Technology, Bachelor of Science (B.Sc.), Information Technology at Hamburg University of Technology (Germany)
Contributions:1 review, 96 commits, 118 PRs in 5 years 3 months
Contributions summary:Michał primarily contributed to recipe updates and the creation of new recipes for the bioconda channel. These contributions included modifying build scripts and updating meta.yaml files for various bioinformatics tools. The user also fixed dependencies, addressed linting problems, and updated existing recipes from external sources.
Contributions:18 PRs, 18 pushes, 2 branches in 13 days
genomeblobinstallationdockermaster
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