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Other literature type . 2026
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Conference object . 2026
License: CC BY
Data sources: Datacite
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Conference object . 2026
License: CC BY
Data sources: Datacite
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Advancing Data Analysis and Software Development for Biomedical Research with Standardized Processes

Authors: Kämpf, Christoph; Scholz, Alexander; Jahnke, Wiebke; Kuhn, Christina Katharina; Reiche, Kristin; Blumert, Conny; Löffler, Dennis; +2 Authors

Advancing Data Analysis and Software Development for Biomedical Research with Standardized Processes

Abstract

Biomedical research fundamentally relies on biological data and uses research software to address scientific questions. Here, a description of the established process landscape at the Department of Medical Bioinformatics at the Fraunhofer Institute for Cell Therapy and Immunology (Fraunhofer IZI) is given. Established standardized procedures are used to ensure consistently high-quality biomedical research that combines the generation of next-generation sequencing data, the use of external data (either public or provided by collaboration partners), and bioinformatic data analysis. To ensure data quality, processes to handle biological material from sample receipt through sequencing library preparation, sequencing, and data handover are implemented. These processes cover a wide array of sequencing techniques, including transcriptome, amplicon-based, genome/exome, single-cell, and spatial sequencing. The data handover process is crucial, as it governs the exchange of data from the laboratory to the analysis domain. When data is transferred to the computing cluster, workflows for primary and secondary analyses, including quality control, are triggered. Data backup occurs in parallel with these steps. Additionally, processes are required to ensure that hardware and software are kept up to date (covering both computing resources and laboratory equipment). These data management processes follow the FAIR principles and are designed to be GDPR-compliant. Finally, the preprocessed data is handed over to the data analysts for downstream analysis. While all analysis code must comply with established coding guidelines, the inherently exploratory nature of biomedical research precludes complete standardization. Once the analysis is complete, the results need to be published. Standardization supports researchers with processes for data and code publication that address legal issues regarding patient privacy and data protection. Further processes are meant to support our collaboration partners with data collection and the establishment of contracts for material and data exchange. The goal of these efforts is to ensure reproducibility of results and legal compliance, thereby easing the path to technology transfer. We are aware of the tension between standardized processes and the exploratory nature of research, with a focus on research software development, and we will address this topic as well.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green