Transcriptomic insights into microbial process adaptation

The BIOSCALE team aims to systematize scale-up in biotechnological processes, thereby enabling reduced development times, higher success rates, and improved process quality for scale-up procedures.

Within this team, I am responsible for the bioinformatic analysis of RNA-Seq data. My focus lies on extracting biologically meaningful insights from large-scale transcriptomic datasets to understand how process conditions shape cellular responses. Beyond differential expression analysis, I am particularly interested in identifying functionally relevant genes that contribute to metabolic adaptation and product formation. By integrating computational biology with process understanding, my work supports a more mechanistic and biology-driven approach to process scale-up.

In addition, my research interests include pathway elucidation, functional gene characterization, and the reuse of publicly available omics data to expand our understanding of microbial metabolism across species.

Grünig, N. & Pucker, B. (2025). CoExpPhylo – a novel pipeline for biosynthesis gene discovery. BMC Genomics 26, 807. https://doi.org/10.1186/s12864-025-12061-3

Grünig, N., Horz, J. M., & Pucker, B. (2024). Diversity and Ecological Functions of Anthocyanins. Preprints; Manuscript under peer review. https://doi.org/10.20944/preprints202408.2272.v1

Pucker, B., Grünig, N., & Khatun, N. (2025). Gene Expression Analysis Across Plantae [dataset]. https://doi.org/10.24355/dbbs.084-202501230512-0

Pucker, B., Fiene, N., Choudhary, N., Borchert, M., & Khatun, N. (2024). Collection of plant gene expression data[dataset]. https://doi.org/10.24355/dbbs.084-202409160820-0