Publications by authors named "H Rasche"

Background: In clinical research, data have to be accessible and reproducible, but the generated data are becoming larger and analysis complex. Here we propose a platform for Findable, Accessible, Interoperable, and Reusable (FAIR) data access and creating reproducible findings. Standardized access to a major genomic repository, the European Genome-Phenome Archive (EGA), has been achieved with API services like PyEGA3.

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Article Synopsis
  • Traditional hands-on training in bioinformatics often struggles with resource-intensive requirements and management issues for instructors, especially in virtual settings where tracking student progress is challenging.
  • The Training Infrastructure-as-a-Service (TIaaS) was developed to provide user-friendly, efficient training resources specifically for Galaxy-based courses, allowing event organizers to allocate dedicated resources for smoother operations and quick job completion.
  • TIaaS enhances the training experience for both instructors and students by offering a dashboard for monitoring progress and ensuring students can seamlessly continue using Galaxy tools even after the training, with significant usage reported over the past 60 months.
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There are thousands of well-maintained high-quality open-source software utilities for all aspects of scientific data analysis. For more than a decade, the Galaxy Project has been providing computational infrastructure and a unified user interface for these tools to make them accessible to a wide range of researchers. To streamline the process of integrating tools and constructing workflows as much as possible, we have developed Planemo, a software development kit for tool and workflow developers and Galaxy power users.

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There is an ongoing explosion of scientific datasets being generated, brought on by recent technological advances in many areas of the natural sciences. As a result, the life sciences have become increasingly computational in nature, and bioinformatics has taken on a central role in research studies. However, basic computational skills, data analysis, and stewardship are still rarely taught in life science educational programs, resulting in a skills gap in many of the researchers tasked with analysing these big datasets.

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Summary: Properly and effectively managing reference datasets is an important task for many bioinformatics analyses. Refgenie is a reference asset management system that allows users to easily organize, retrieve and share such datasets. Here, we describe the integration of refgenie into the Galaxy platform.

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