Marco Galardini is an associate professor and computational biologist with 14 years of experience building large-scale genotype-to-phenotype pipelines and open-source tools for microbial genomics. Based in Hanover, he leads research at the intersection of comparative genomics, clinical and environmental microbiology, and evolutionary biology within the RESIST cluster and Twincore. He combines deep Python expertise and hands-on lab experience from postdoctoral work at EMBL-EBI and Boston University to translate high-throughput phenotyping and sequencing data into reproducible analyses and software. An active open-source contributor, he has improved core community tools such as Biopython (phenotype module) and Roary visualizations, reflecting a focus on practical data formats, plotting, and interoperability. He also brings an unexpected creative side—DIY music and small experiments—that feeds a curious, multidisciplinary approach to research and mentorship.
14 years of coding experience
1 year of employment as a software developer
Training, Bioinformatics, Training, Bioinformatics at Radboud University
Master’s Degree, Bioinformatics, Master’s Degree, Bioinformatics at Alma Mater Studiorum – Università di Bologna
Doctor of Philosophy (Ph.D.), Bioinformatics, Doctor of Philosophy (Ph.D.), Bioinformatics at Università degli Studi di Firenze
Contributions:8 commits, 6 PRs, 14 comments in 2 years 2 months
Contributions summary:Marco primarily contributed to the `roary_plots` component, focusing on the visualization of pan-genome data. Their work included adding node labels to phylogenetic trees, fixing display issues in the HTML and notebook outputs, and adding the ability to save plots in multiple formats. They also addressed deprecated functions in pandas and adjusted the tree positioning.
Official git repository for Biopython (originally converted from CVS)
Role in this project:
Back-end Developer
Contributions:1 review, 12 commits, 3 PRs in 1 month
Contributions summary:Marco primarily contributed to the `BioPython` library, focusing on the `phenotype` module. They introduced new functionality for handling Phenotype Microarray data, including classes for `PlateRecord` and `WellRecord` objects. The user also implemented JSON serialization and deserialization of the plate data, along with associated unit tests, improving the library's data input/output capabilities. Further contributions included improving the fitting method and associated tests for the WellRecord class.
git-repositoryphylogeneticspythondnagenomics
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