Bioinformatics

Turning biological data into sustainable solutions

We combine omics technologies with AI-driven data analysis to translate raw biological data into actionable knowledge — for sustainable agriculture, biotechnology, environmental protection, and regulatory compliance.

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Key benefits: For Industry and Research Partners

  • Faster decision making through intelligent data integration
  • Reduced Research&Development  costs by targeted analysis instead of trial and error
  • Higher success rates in product development and process optimization
  • Regulatory-ready insights for safety, efficacy, and environmental impact
  • End-to-end support from experimental design to validated results

Your data + our expertise = reliable knowledge for real-world impact

 

How it works (pipeline section)

From raw data to actionable insight in four steps

 

1. Data Acquisition & Integration

  • Multi-omics (genomics, transcriptomics, proteomics, metabolomics)
  • Environmental and phenotypic data
  • Public databases and client data

2. Quality Control & Standardization

  • Automated data cleaning
  • Harmonization of formats
  • Reproducible workflows

3. AI-Driven Analysis

  • Machine learning and statistical modeling
  • Biomarker discovery
  • Predictive analytics
  • Network and pathway analysis

4. Interpretation & Reporting

  • Clear visualizations
  • Biological interpretation
  • Decision-ready reports

 

Key Capabilities 

 

Data Types

  • Genomics & metagenomics
  • Transcriptomics
  • Proteomics
  • Metabolomics
  • Environmental sequencing
  • Imaging and phenotypic data

Methods & Technologies

  • Systems biology modeling
  • Statistical analysis
  • Data visualization dashboards
  • Automated pipelines
  • FAIR data management
  • Machine learning & deep learning

Application Areas

  • Sustainable biotechnology
  • Environmental monitoring
  • Toxicology and safety assessment
  • Microbiome research
  • Plant and agricultural sciences
  • Regulatory science

 

 

 

Selected Publications

Roelfs KU., Känel A., Twyman R.M., Prüfer D., Schulze Gronover C.
Epigenetic variation in early and late flowering plants of the rubber-producing Russian dandelion Taraxacum koksaghyz provides insights into the regulation of flowering time
(2024) Scientific Reports 14, 4283  https://doi.org/10.1038/s41598-024-54862-8

 

Solís, J. L., Muth, J., Canales, J., Lizana, C., Pruefer, D., Riegel, R., & Behn, A.
Allelic diversity of three anthocyanin synthesis genes in accessions of native Solanum tuberosum L. ssp. tuberosum at the Potato Genebank of the Universidad Austral de Chile.
(2022) Genetic resources and crop evolution, 69(1), 297-314. https://doi.org/10.1007/s10722-021-01230-4

 

Benninghaus, V.A., Van Deenen, N., Müller, B., Roelfs, K.-U., Lassowskat, I., Finkemeier, I., Prüfer, D., Gronover, C.S.
Comparative proteome and metabolome analyses of latex-exuding and non-exuding Taraxacum koksaghyz roots provide insights into laticifer biology
(2020) Journal of Experimental Botany, 71 (4), 1278-1293. https://doi.org/10.1093/jxb/erz512

 

Riekötter, J, Oklestkova, J, Muth, J, Twyman, RM, Epping, J
Transcriptomic analysis of Chinese yam (Dioscorea polystachya Turcz.) variants indicates brassinosteroid involvement in tuber development 
(2023) Frontiers Nutrition https://doi.org/10.3389/fnut.2023.1112793

 

Känel A, Roelfs KU, Wissing M, Lenzen B, Klein M, Twyman RM, Noll GA, Prüfer D
Vernalization reveals distinct roles of FLOWERING LOCUS T homologs in floral transition of perennial Taraxacum koksaghyz  
(2026) Plant Science 112743 https://doi.org/10.1016/j.plantsci.2025.112743

 

Mäckelmann S., Känel A., Kösters L.M., Lyko P., Prüfer D., Noll G.A., Wicke S.
Gene complementation analysis indicates that parasitic dodder plants do not depend on the host FT protein for flowering
(2024) Plant Communications https://doi.org/10.1016/j.xplc.2024.100826