Saskia Hiltemann

The paper introduces the Microbiology Galaxy Lab, a community-driven platform for reproducible and FAIR microbial data analysis, offering tools for various omics data types and use cases.

The paper updates TAPscan to enhance sensitivity, enabling analysis of transcription factor evolution in streptophyte algae and land plants, identifying lineage-specific gains.

The paper introduces Galaxy Training Network (GTN) as a framework for creating and sharing FAIR training materials for data analysis, with recent improvements to support educators and expand its use in various learning environments.

TIaaS provides scalable infrastructure for efficient bioinformatics training, enabling remote and in-person classes with minimal delays and administrative overhead.

The paper presents a community-driven framework for interactive data analytics training in life sciences, enabling researchers to learn through web-based computation without software installation.

ASaiM provides a Galaxy-based framework for analyzing microbiota data, offering curated tools and workflows for taxonomic and functional analysis of raw sequencing data.