Mark Diekhans
Computional Genomics Engineer at UC Santa Cruz Genomics Institute
California, United States
Summary
🤩
Rockstar🎓
Top SchoolMark Diekhans is a computational genomics engineer with over 16 years of focused experience building robust bioinformatics infrastructure at institutions like UC Santa Cruz Genomics Institute and Stanford. He combines deep software engineering roots dating back to HP and SCO with specialized work on genome alignment and workflow engines, contributing build- and deployment-critical fixes to projects such as the Cactus aligner and the scalable Toil workflow engine. Mark’s strengths are in backend systems, reproducible builds, and making HPC batch integrations (SLURM, GridEngine) more reliable and debuggable—skills that keep complex pipelines running in production. Based in California, he bridges academic research and production engineering, translating genomics algorithms into maintainable software. An under-the-radar asset is his long-standing focus on build systems and dependency management, a niche that prevents subtle failures in large-scale comparative genomics workflows.
16 years of coding experience
22 years of employment as a software developer
bs, computer science, bioilogy, bs, computer science, bioilogy at Indiana University Bloomington
Github Skills (17)
slurm10
python10
workflow-engine10
c1110
batchfile10
makefile10
c1710
batch10
devops10
batch-processing10
cicd9
build-system9
automation9
automations9
dependency-management8
Programming languages (25)
Github contributions (5)
ComparativeGenomicsToolkit/cactus
Apr 2011 - Oct 2022
Official home of genome aligner based upon notion of Cactus graphs
Role in this project:
Backend Developer
Backend DeveloperContributions:2 releases, 1 review, 167 commits in 11 years 8 months
Contributions summary:Mark primarily focused on fixing build and compilation issues within the Cactus genome aligner project. They addressed recursive make calls and dependencies, indicating an effort to improve the build process. Additionally, the user made changes to the setup files and included libraries, which suggests involvement in the project's build system and dependency management. These contributions directly improved the build process and helped keep it functional.
genomenotioncactusalignergenomics
DataBiosphere/toil
Feb 2018 - Apr 2020
A WDL, CWL and Python API supporting easy-to-use workflow engine. It is scalable, efficient and cross-platform (Linux/macOS).
Role in this project:Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:24 commits, 11 PRs, 32 pushes in 2 years 2 months
Contributions summary:Mark primarily contributed to improving the robustness and debuggability of the batch system integration within the workflow engine. This included adding logging, error checking, and implementing more reliable command execution for different HPC batch systems like SLURM and GridEngine. Furthermore, the user enhanced the system's ability to handle various states and exit codes from the batch systems, ensuring more reliable job status updates. The user also made changes to address configuration issues, specifically related to CPU and memory resource allocation, by correctly handling environment variables for parallel execution environments.
linuxmacospythonwdlworkflow-engine
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