Bioinformatics

How it works (pipeline section)

From raw data to actionable insight in four steps

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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 modelling
  • Biomarker discovery
  • Predictive analytics
  • Network and pathway analysis

4. Interpretation & Reporting

  • Clear visualizations
  • Biological interpretation
  • Decision-ready reports

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.

Key Capabilities

Data Types

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



Methods & Technologies

  • Systems biology modelling
  • 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



Call to Action

Let’s turn your data into solutions.

 

  • Have a dataset but don’t know where to start?
  • Planning an omics experiment?
  • Need AI-driven insights for a project?

 

Contact us for a free initial consultation.

Selected Publications

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

 

Essfeld, F., Ayobahan, S.U., Strompen, J., Alvincz, J., Schmidt-Posthaus, H., Woelz, J., Mueller, T., Ringbeck, B., Teigeler, M., Eilebrecht, E., Eilebrecht, S.
Transcriptomic Point of Departure (tPOD) of androstenedione in zebrafish embryos as a potential surrogate for chronic endpoints
(2024) Science of the Total Environment. doi.org/10.1016/j.scitotenv.2024.176026

 

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

 

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

 

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

 

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