Publications
In the following, you can find a list of highlighted publications with short summaries. For all publications, please see my Google Scholar profile.
paper: Kuehl M, Schaub DP, Carli F, Heumos L, Hellmig M, Fernández-Zapata C, Kaiser N, Schaul J, Kulaga A, Usanov N, Scverse Community, Krebs CF, Panzer U, Bonn S, Lobentanzer S§, Saez-Rodriguez J§, Puelles VG§ (2025) BioContextAI is a community hub for agentic biomedical systems Nature Biotechnology 43, 1755–1757. doi: https://doi.org/10.1038/s41587-025-02900-9. (§: co-senior authors)
Registry for MCP servers for the use in biomedical AI systems. https://biocontext.ai
paper: Jarchow H, Bobrowski C, Falk S, Hermann A, Kulaga A, Põder J-C, Unfried M, Usanov N, Zendeh B, Kennedy BK#, Lobentanzer S#, Fuellen G# (2025) Benchmarking large language models for personalized, biomarker-based health intervention recommendations npj Digit. Med. 8, 631. doi: https://doi.org/10.1038/s41746-025-01996-2. (#: corresponding authors)
Benchmarking study on LLM-as-a-judge application to medical question answering.
paper: Lobentanzer S#, Feng S, Bruderer N, Maier A, BioChatter Consortium, Wang C, Baumbach J, Abreu-Vicente J, Krehl N, Ma Q, Lemberger T, Saez-Rodriguez J# (2025) A platform for the biomedical application of large language models Nature Biotechnology 43, 166–169. doi: https://doi.org/10.1038/s41587-024-02534-3. (#: corresponding authors)
Peer-reviewed version of the preprint from 2023. More info at http://biochatter.org.
perspective: Lobentanzer S#, Rodriguez-Mier P, Bauer S, Saez-Rodriguez J# (2024) Molecular causality in the advent of foundation models Molecular Systems Biology 20, 848–858. doi: https://doi.org/10.1038/s44320-024-00041-w. (#: corresponding authors)
Exploration of and perspective on the tradeoff between simplicity and complexity in molecular modelling, with a focus on current trends in deep learning and their potential application in causal inference.
preprint: Lobentanzer S#, Saez-Rodriguez J# (2023) A platform for the biomedical application of Large Language Models arXiv. doi: https://arxiv.org/abs/2305.06488 (#: corresponding authors)
BioChatter is an extension of the BioCypher ecosystem that enables the modular integration of Large Language Models into biomedical workflows. Its prototype frontends (https://chat.biocypher.org) demonstrate some capabilities of the framework in facilitating human-machine collaboration.
paper: Lobentanzer S#, BioCypher Consortium, Saez-Rodriguez J# (2023) Democratizing knowledge representation with BioCypher Nature Biotechnology 41, 1056–1059. doi: https://www.nature.com/articles/s41587-023-01848-y, openly available at https://zenodo.org/records/10320714. (#: corresponding authors)
Publication introducing the BioCypher framework, a modular and extensible knowledge representation framework written in Python. The framework is designed to be accessible to non-experts and to facilitate the integration of knowledge from different sources.
review: Garrido-Rodriguez M, Zirngibl K, Ivanova O, Lobentanzer S, Saez-Rodriguez J (2022) Integrating knowledge and omics to decipher mechanisms via large-scale models of signaling networks Molecular Systems Biology 18, MSB202211036. doi: https://doi.org/10.15252/msb.202211036.
An overview of computational methods to evaluate signal transduction at the protein interaction layer. Briefly, the methods are heterogeneous in design as well as in purpose, and a medium-term objective should be the harmonisation and benchmarking of these methods to establish a baseline for the performance of signal propagation network modelling in molecular biology.
monograph: Lobentanzer S (2020) Small RNA Dynamics in Cholinergic Systems. Dissertation, defended 2nd of October 2020 (summa cum laude), available at http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/56125.
The magnum opus from my PhD. In large parts related to the 2019 Cell Reports paper and the 2020 PNAS paper.
paper: Lobentanzer S, Klein J, Soreq H (2020) Establishing human male and female models of cholinergic neurons via neurokine-mediated differentiation of LA-N-2 and LA-N-5 neuroblastoma cells. STAR Protocols, 1 (3), doi: https://doi.org/10.1016/j.xpro.2020.100193.
Elaboration on the cell culture developed for the 2019 Cell Reports paper.
paper: Winek K†, Lobentanzer S†, Nadorp B, Dubnov S, Dames C, Jagdmann S, Moshitzky G, Hotter B, Meisel C, Greenberg DS, Shifman S, Klein J, Shenhar-Tsarfaty S, Meisel A, Soreq H (2020) Transfer RNA fragments replace microRNA regulators of the cholinergic post-stroke immune blockade. Proc. Natl. Acad. Sci., 117 (51) 32606-32616, doi: https://doi.org/10.1073/pnas.2013542117. (†: equal contribution)
The second major publication resulting from my PhD. Small RNA species observed after a sizeable infarction in the brain of human patients show distinct pattern shifts between microRNAs and tRNA-derived fragments. While the functional implications are as yet unclear, tRNA fragments are an interesting emerging regulatory mechanism with potential of fast (immediate early-type) response times. We elucidated the background of several candidate molecules found and developed ways of validating their relevance in human- and mouse-derived experiments.
paper: Lobentanzer S, Hanin G, Klein J, Soreq H (2019) Integrative Transcriptomics Reveals Sexually Dimorphic Control of the Cholinergic/Neurokine Interface in Schizophrenia and Bipolar Disorder. Cell Reports 29(3):764-777.e5, doi: https://doi.org/10.1016/j.celrep.2019.09.017.
The first major publication resulting from my PhD. Informed by a meta-analysis of human brain transcriptome samples and single-cell expression patterns, we develop a human neuronal cell culture system to study small RNA dynamics under cholinergic differentiation caused by neurokines. We identify families of microRNAs related to the differentiation process, which we cross-reference with disease processes in psychiatric diseases. In vitro interventional experiments confirm predictions of the pivotal microRNA miR-125b-5p in transcriptional cholinergic regulation.