Prof. Dr. Jana Schor
(née Hertel)
Head of Bio-Data Science
Helmholtz Centre for Environmental Research - UFZ
Department Computational Biology
Permoserstr. 15
04318 Leipzig
GERMANY
Building: Building 4.1
Room: Room 238
Phone: +49 341 235 4779
Email: jana.schor@ufz.de
Curriculum Vitae
Current position
Head of Bio-Data Science Group, Department Computational Biology and Chemistry
Professorship
Bio-Data Science, Faculty of Mathematics and Computer Science, University of Leipzig, Germany
Previous position
Head of Bioinformatics, Department Computational Biology
Scientific degrees
- Professorship Bio-Data Science (2024)
- PhD Computer Science / Bioinformatics (2008)
- Diploma Computer Science (2005)
Research:
My research centers on advancing Data Science methodologies—such as Statistical, Machine, Deep Learning, and Data Analysis and Integration—to unlock deeper insights from expansive Big Data in human and environmental health. By developing and applying cutting-edge computational techniques, I aim to broadly generate novel hypotheses and predictive models, particularly within ecological and health research domains. A core focus of my work is to bolster the credibility of AI-driven analyses by embedding explainability and quantifiable uncertainty measures into each application. Additionally, I strongly emphasize reproducible research, ensuring that findings are transparent, consistent, and valuable for the scientific community.
- Data integration and analysis via graph databases
- Graph neural networks, explainability, and quantification of uncertainty to improve computational predictions
- Grounding LLMs with domain-specific knowledge graphs for enhanced data accessibility
Infrastructure, programs and approaches:
- High-performance computing clusters for large-scale data processing.
- Training AI on GPUs to accelerate model performance.
- Graph and other neural networks for complex, interconnected data structures (for supervised, unsupervised, and reinforcement learning tasks).
- Knowledge graphs and graph databases for data organization and semantic relationships.
- Large language models to enhance interpretability and applications in research.
- Programming languages like R, Python, shell scripting, awk, Cypher, and SQL for versatile data manipulation and analysis.
Teaching and educational offers:
In addition to my research, I am dedicated to teaching future data scientists and computer science students. Via the university Leipzig, I offer courses in statistical learning, R programming, and an interactive Data Science curriculum designed to prepare students comprehensively for the field. These courses include:
- Hands-on training in R and Python,
- Version control with Git,
- Agile project and self-management practices,
- Storytelling with data,
- Crafting compelling and representative visuals and
- Developing strong presentation skills.
- I aim to equip students with a robust, practical skill set that prepares them for success in real-world data science roles.
Publications
My five recent most essential publications are sorted by relevance:
- Schor, J., Scheibe, P., Bernt, M., Busch, W., Lai, C., Hackermüller, J. (2022):
AI for predicting chemical-effect associations at the chemical universe level — deepFPlearn
Brief. Bioinform. 23 (5), bbac257 10.1093/bib/bbac257 - Soulios, K., Scheibe, P., Bernt, M., Hackermüller, J., Schor, J. (2023):
deepFPlearn+: enhancing toxicity prediction across the chemical universe using graph neural networks
Bioinformatics 39 (12), btad713 10.1093/bioinformatics/btad713 - Canzler, S., Schor, J., Busch, W., Schubert, K., Rolle-Kampczyk, U.E., Seitz, H., Kamp, H., von Bergen, M., Buesen, R., Hackermüller, J. (2020):
Prospects and challenges of multi‑omics data integration in toxicology
Arch. Toxicol. 94 (2), 371 - 388 10.1007/s00204-020-02656-y - Völkner, M., Wagner, F., Steinheuer, L.M., Carido, M., Kurth, T., Yazbeck, A., Schor, J., Wieneke, S., Ebner, L.J.A., Del Toro Runzer, C., Taborsky, D., Zoschke, K., Vogt, M., Canzler, S., Hermann, A., Khattak, S., Hackermüller, J., Karl, M.O. (2022):
HBEGF-TNF induce a complex outer retinal pathology with photoreceptor cell extrusion in human organoids
Nat. Commun. 13 , art. 6183 10.1038/s41467-022-33848-y - Gutsfeld, S., Wehmas, L., Omoyeni, I.E., Schweiger, N., Leuthold, D., Michaelis, P., Howey, X.M., Gaballah, S., Herold, N., Vogs, C., Wood, C., Bertotto, L., Wu, G.-M., Klüver, N., Busch, W., Scholz, S., Schor, J., Tal, T. (2024):
Investigation of peroxisome proliferator-activated receptor genes as requirements for visual startle response hyperactivity in larval zebrafish exposed to structurally similar per- and polyfluoroalkyl substances (PFAS)
Environ. Health Perspect. 132 (7), art. 077007 10.1289/EHP13667
Index:
You could use our publication index for further requests.
2025 (4)
- Canzler, S., Lehmann, J., Schor, J., Busch, W., Hackermüller, J. (2025):
From toxicogenomics data to cumulative assessment groups: A mechanistic framework for chemical grouping
bioRxiv 10.1101/2025.01.24.634648 - Gad, M., Tayyebi Sabet Khomami, N., Krieg, R., Schor, J., Philippe, A., Lechtenfeld, O.J. (2025):
Environmental drivers of dissolved organic matter composition across central European aquatic systems: A novel correlation-based machine learning and FT-ICR MS approach
Water Res. 273 , art. 123018 10.1016/j.watres.2024.123018 - Mutlu, İ., Hackermüller, J., Schor, J. (2025):
Automated curation of spatial metadata in environmental monitoring data
Ecol. Inform. 86 , art. 103038 10.1016/j.ecoinf.2025.103038 - Schor, J., Mutlu, İ., Busch, W., Bumberger, J., Schulze, T., Ulrich, N., Hassan, K.N., Krauss, M., Brack, W., Doan, T., Bingert, S., Hackermüller, J. (2025):
Neo4j Container Link for the Curated Dataset in ChEOS Project [Data set]
Zenodo 10.5281/zenodo.14616124
2024 (4)
- Aldehoff, A.S., Karkossa, I., Goerdeler, C., Krieg, L., Schor, J., Engelmann, B., Wabitsch, M., Landgraf, K., Hackermüller, J., Körner, A., Rolle-Kampczyk, U., Schubert, K., von Bergen, M. (2024):
Unveiling the dynamics of acetylation and phosphorylation in SGBS and 3T3-L1 adipogenesis
iScience 27 (6), art. 109711 10.1016/j.isci.2024.109711 - Gutsfeld, S., Wehmas, L., Omoyeni, I.E., Schweiger, N., Leuthold, D., Michaelis, P., Howey, X.M., Gaballah, S., Herold, N., Vogs, C., Wood, C., Bertotto, L., Wu, G.-M., Klüver, N., Busch, W., Scholz, S., Schor, J., Tal, T. (2024):
Investigation of peroxisome proliferator-activated receptor genes as requirements for visual startle response hyperactivity in larval zebrafish exposed to structurally similar per- and polyfluoroalkyl substances (PFAS)
Environ. Health Perspect. 132 (7), art. 077007 10.1289/EHP13667 - Mutlu, İ., Schor, J. (2024):
Chemical occurence data curation results with CleanGeoStreamR
Zenodo 10.5281/zenodo.13799955 - Mutlu, İ., Schor, J. (2024):
Collection of chemical occurance data from NORMAN surface water database and other related files
Zenodo 10.5281/zenodo.11395194
2023 (2)
- Soulios, K., Scheibe, P., Bernt, M., Hackermüller, J., Schor, J. (2023):
deepFPlearn+: enhancing toxicity prediction across the chemical universe using graph neural networks
Bioinformatics 39 (12), btad713 10.1093/bioinformatics/btad713 - Soulios, K., Scheibe, P., Bernt, M., Hackermüller, J., Schor, J. (2023):
deepFPlearn+
Zenodo 10.5281/zenodo.8146252
2022 (4)
- Schor, J., Scheibe, P., Bernt, M., Busch, W., Lai, C., Hackermüller, J. (2022):
AI for predicting chemical-effect associations at the chemical universe level — deepFPlearn
Brief. Bioinform. 23 (5), bbac257 10.1093/bib/bbac257 - Schor, J., Yazbeck, A.M, Völkner, M., Hackermüller, J., Karl, M.O. (2022):
HBEGF-TNF induces a complex retinal pathology with macular degeneration hallmarks in human organoids
Gene Expression Omnibus - Velandia-Huerto, C.A., Yazbeck, A.M., Schor, J., Stadler, P.F. (2022):
Evolution and phylogeny of microRNAs — Protocols, pitfalls, and problems
In: Allmer, J., Yousef, M. (eds.)
miRNomics. MicroRNA biology and computational analysis
Methods in Molecular Biology 2257
Springer Nature, p. 211 - 233 10.1007/978-1-0716-1170-8_11 - Völkner, M., Wagner, F., Steinheuer, L.M., Carido, M., Kurth, T., Yazbeck, A., Schor, J., Wieneke, S., Ebner, L.J.A., Del Toro Runzer, C., Taborsky, D., Zoschke, K., Vogt, M., Canzler, S., Hermann, A., Khattak, S., Hackermüller, J., Karl, M.O. (2022):
HBEGF-TNF induce a complex outer retinal pathology with photoreceptor cell extrusion in human organoids
Nat. Commun. 13 , art. 6183 10.1038/s41467-022-33848-y
Index:
You could use our publication index for further requests.
2021 (2)
- Schubert, K., Karkossa, I., Schor, J., Engelmann, B., Steinheuer, L.M., Bruns, T., Rolle-Kampczyk, U., Hackermüller, J., von Bergen, M. (2021):
A multi-omics analysis of mucosal-associated-invariant T cells reveals key drivers of distinct modes of activation
Front. Immunol. 12 , art. 616967 10.3389/fimmu.2021.616967 - Völkner, M., Kurth, T., Schor, J., Ebner, L.J.A., Bardtke, L., Kavak, C., Hackermüller, J., Karl, M.O. (2021):
Mouse retinal organoid growth and maintenance in longer-term culture
Front. Cell. Dev. Biol. 9 , art. 645704 10.3389/fcell.2021.645704
2020 (3)
- Balogh, G., Bernhart, S.H., Stadler, P.F., Schor, J. (2020):
A probabilistic version of Sankoff’s maximum parsimony algorithm
J. Bioinform. Comput. Biol. 18 (1), art. 2050004 10.1142/S0219720020500043 - Canzler, S., Schor, J., Busch, W., Schubert, K., Rolle-Kampczyk, U.E., Seitz, H., Kamp, H., von Bergen, M., Buesen, R., Hackermüller, J. (2020):
Prospects and challenges of multi‑omics data integration in toxicology
Arch. Toxicol. 94 (2), 371 - 388 10.1007/s00204-020-02656-y - Olms, C., Schor, J., Yahiaoui-Doktor, M. (2020):
Potential co-factors of an intraoral contact allergy — A cross-sectional study
Dent. J. 8 (3), art. 83 10.3390/dj8030083
2019 (3)
- Bauer, M., Hackermüller, J., Schor, J., Schreiber, S., Fink, B., Pierzchalski, A., Herberth, G. (2019):
Specific induction of the unique GPR15 expression in heterogeneous blood lymphocytes by tobacco smoking
Biomarkers 24 (3), 217 - 224 10.1080/1354750X.2018.1539769 - Kämpf, C., Specht, M., Scholz, A., Puppel, S.-H., Doose, G., Reiche, K., Schor, J., Hackermüller, J. (2019):
uap: reproducible and robust HTS data analysis
BMC Bioinformatics 20 , art. 664 10.1186/s12859-019-3219-1 - Schubert, K., Schor, J., Kratochvil, I., Hackermüller, J., von Bergen, M. (2019):
Multi-omics profiling of MAIT cells reveals specific patterns of antigen-dependent and -independent activation
Eur. J. Immunol. 49 (Suppl. 1), 141 10.1002/eji.201970300
2018 (1)
- Canzler, S., Stadler, P.F., Schor, J. (2018):
The fungal snoRNAome
RNA 24 (3), 342 - 360 10.1261/rna.062778.117
2017 (2)
- Canzler, S., Stadler, P.F., Hertel, J. (2017):
Evolution of fungal U3 snoRNAs: Structural variation and introns
Non-Coding RNA 3 (1), art. 3 10.3390/ncrna3010003 - Yazbeck, A.M., Tout, K.R., Stadler, P.F., Hertel, J. (2017):
Towards a consistent, quantitative evaluation of microRNA evolution
J. Integr. Bioinform. 14 (1) 10.1515/jib-2016-0013
2016 (5)
- Bhattacharya, D.P., Canzler, S., Kehr, S., Hertel, J., Grosse, I., Stadler, P.F. (2016):
Phylogenetic distribution of plant snoRNA families
BMC Genomics 17 , art. 969 10.1186/s12864-016-3301-2 - Braasch, I., Gehrke, A.R., Smith, J.J., Kawasaki, K., Manousaki, T., Pasquier, J., Amores, A., Desvignes, T., Batzel, P., Catchen, J., Berlin, A.M., Campbell, M.S., Barrell, D., Martin, K.J., Mulley, J.F., Ravi, V., Lee, A.P., Nakamura, T., Chalopin, D., Fan, S., Wcisel, D., Cañestro, C., Sydes, J., Beaudry, F.E.G., Sun, Y., Hertel, J., Beam, M.J., Fasold, M., Ishiyama, M., Johnson, J., Kehr, S., Lara, M., Letaw, J.H., Litman, G.W., Litman, R.T., Mikami, M., Ota, T., Saha, N.R., Williams, L., Stadler, P.F., Wang, H., Taylor, J.S., Fontenot, Q., Ferrara, A., Searle, S.M.J., Aken, B., Yandell, M., Schneider, I., Yoder, J.A., Volff, J.-N., Meyer, A., Amemiya, C.T., Venkatesh, B., Holland, P.W.H., Guiguen, Y., Bobe, J., Shubin, N.H., Di Palma, F., Alföldi, J., Lindblad-Toh, K., Postlethwait, J.H. (2016):
The spotted gar genome illuminates vertebrate evolution and facilitates human-teleost comparisons
Nature Genet. 48 (4), 427 - 437 10.1038/ng.3526 - Canzler, S., Stadler, P.F., Hertel, J. (2016):
U6 snRNA intron insertion occurred multiple times during fungi evolution
RNA Biol. 13 (2), 119 - 127 10.1080/15476286.2015.1132139 - de Araujo Oliveira, J.V., Costa, F., Backofen, R., Stadler, P.F., Walter, M.E.M.T., Hertel, J. (2016):
SnoReport 2.0: new features and a refined Support Vector Machine to improve snoRNA identification
BMC Bioinformatics 17 (Suppl 18), art. 464 10.1186/s12859-016-1345-6 - Fontenot, Q., Ferrara, A., Searle, S.M.J., Aken, B., Yandell, M., Schneider, I., Yoder, J.A., Volff, J.-N., Meyer, A., Amemiya, C.T., Venkatesh, B., Holland, P.W.H., Guiguen, Y., Bobe, J., Shubin, N.H., Di Palma, F., Alföldi, J., Lindblad-Toh, K., Postlethwait, J.H., Martin, K.J., Mulley, J.F., Ravi, V., Lee, A.P., Nakamura, T., Chalopin, D., Fan, S., Wcisel, D., Cañestro, C., Sydes, J., Beaudry, F.E.G., Sun, Y., Hertel, J., Beam, M.J., Fasold, M., Ishiyama, M., Johnson, J., Kehr, S., Lara, M., Letaw, J.H., Litman, G.W., Litman, R.T., Mikami, M., Ota, T., Saha, N.R., Williams, L., Stadler, P.F., Wang, H., Taylor, J.S., Braasch, I., Gehrke, A.R., Smith, J.J., Kawasaki, K., Manousaki, T., Pasquier, J., Amores, A., Desvignes, T., Batzel, P., Catchen, J., Berlin, A.M., Campbell, M.S., Barrell, D. (2016):
Corrigendum: The spotted gar genome illuminates vertebrate evolution and facilitates human-teleost comparisons (vol 48, pg 427, 2016)
Nature Genet. 48 (6), 700 - 700 10.1038/ng0616-700c
For older publications processed at the Uni Leipzig and/or Uni Wien under my birth name Jana Hertel
Professur für Bioinformatik
Institut für Informatik
Universität Leipzig
Härtelstr. 16-18
D-04107 Leipzig
Institut für Theoretische Chemie
Universität Wien
Währinger Straße 17
A-1090 Wien
please refer to my ORCID profile.