Daniel Blankenberg is an Associate Staff software engineer and bioinformatics developer with 19 years of experience bridging computational biology and robust backend engineering. Based at the Cleveland Clinic, he has a PhD in Biochemistry, Microbiology and Molecular Biology and a strong dual background in computer science from Gettysburg College, enabling him to translate complex 'omics problems into production-ready tools. He is an active open-source contributor to major community platforms like anvi'o and Galaxy, where his backend work has improved tool loading, data handling, and reproducibility for the wider bioinformatics community. Known for pragmatic bug fixes and feature implementations, he also maintains tool repositories and helps onboard new computational tools—skills he leverages when hiring and mentoring postdocs and developers.
19 years of coding experience
7 years of employment as a software developer
Ph.D., Biochemistry, Microbiology and Molecular Biology, Ph.D., Biochemistry, Microbiology and Molecular Biology at Penn State University
B.S., Biochemistry & Molecular Biology and Computer Science, B.S., Biochemistry & Molecular Biology and Computer Science at Gettysburg College
Tool Shed repositories maintained by the Intergalactic Utilities Commission
Role in this project:
Back-end Developer & Tools Maintainer
Contributions:18 reviews, 118 commits, 63 PRs in 8 years 1 month
Contributions summary:Daniel primarily contributed to the development and maintenance of tools within the Galaxy project's tool shed. Their work focused on adding new tools, such as those for scikit-bio and Kraken taxonomy reporting, as well as biom-format tools. They also updated existing tools, including the kraken_taxonomy_report, and made code improvements such as incorporating `from __future__ import print_function` and fixing URLs.
Contributions:9 reviews, 1 commit, 268 PRs in 1 day
Contributions summary:Daniel primarily contributed to the back-end code of the Galaxy project, focusing on enhancing the functionality of tool loading and data handling. Their work included fixing bugs related to hidden directories, Python3 compatibility, and refgenie data table integration. They also improved debug logging and made changes to data display applications. Several commits involved configuration updates and dependency management.
pythonsciencepipelinednadata-science
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