Lea Seep
Affiliations
  • Life and Medical Sciences Institute (LIMES)
Research topics
  • Machine Learning
Lea Seep has done her Bachelor’s degree in Molecular Biomedicine in Bonn, starting to gain insights into the field of bioinformatics during her bachelor thesis. To further explore the field of life-science related informatics she conducted a full-time work experience at Bayer for 6 months within the Computational Chemistry group, before conducting her M.Sc. in Bioinformatics at the University of Potsdam. There she was introduced to constraint-based modelling, machine learning, systems-biology and network analysis. In her Master thesis she combined network analysis, statistical analysis and classical machine learning to search for patterns explaining a certain biological phenomena. She has joined the group of Prof. Hasenauer as PhD student in December 2021.
Selected publications

Huang, H., Balzer, N.R., Seep, L. et al. Kupffer cell programming by maternal obesity triggers fatty liver disease. Nature (2025). https://doi.org/10.1038/s41586-025-09190-w

Seep, L. et al. cOmicsArt—a customizable Omics Analysis and reporting tool, Bioinformatics Advances, Volume 5, Issue 1, 2025, vbaf067, https://doi.org/10.1093/bioadv/vbaf067

Seep, L., Grein, S., Splichalova, I. et al. From Planning Stage Towards FAIR Data: A Practical Metadatasheet For Biomedical Scientists. Sci Data 11, 524 (2024). https://doi.org/10.1038/s41597-024-03349-2

Seep, L., Razaghi-Moghadam, Z., Nikoloski, Z. Reaction lumping in metabolic networks for application with thermodynamic metabolic flux analysis. (2021). https://doi.org/10.1038/s41598-021-87643-8

Seep, L. , Bonin, A., Meier, K., Göller, A. H. Ensemble Completeness in Conformer Sampling: Small Macrocycles. (2021). https://doi.org/10.1186/s13321-021-00524-0

Lea Seep

Endenicher Allee 64

53115 Bonn

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