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DE LANDTSHEER Sébastien

University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)

Main Referenced Co-authors
SAUTER, Thomas  (10)
LUCARELLI, Philippe  (4)
BADKAS, Apurva  (3)
SCHNEIDER, Jochen  (3)
Demuth, Ilja (2)
Main Referenced Keywords
machine learning (3); aging (2); biomarker (2); frailty (2); prediction (2);
Main Referenced Unit & Research Centers
ULHPC - University of Luxembourg: High Performance Computing (4)
University of Luxembourg: The Faculty of Science, Technology and Communication (FSTC) (1)
Main Referenced Disciplines
Life sciences: Multidisciplinary, general & others (6)
Geriatrics (2)
Biochemistry, biophysics & molecular biology (2)
Computer science (1)
Immunology & infectious disease (1)

Publications (total 12)

The most downloaded
799 downloads
De Landtsheer, S. (2019). Optimization of logical networks for the modelling of cancer signalling pathways [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/39574 https://hdl.handle.net/10993/39574

The most cited

16 citations (OpenCitations)

De Landtsheer, S. (2015). Near Full-Length Characterization and Population Dynamics of the Human Immunodeficiency Virus Type I Circulating Recombinant Form 42 (CRF42_BF) in Luxembourg. AIDS Research and Human Retroviruses. doi:10.1089/aid.2014.0364 https://hdl.handle.net/10993/26351

Badkas, A., de Landtsheer, S., & Sauter, T. (2023). Expanding the Disease Network of Glioblastoma Multiforme via Topological Analysis. International Journal of Molecular Sciences, 24 (4). doi:10.3390/ijms24043075
Peer reviewed

Didier, J., de Landtsheer, S., Pires Pacheco, M. I., Kishk, A., Schneider, J., Demuth, I., & Sauter, T. (26 October 2022). Improving Machine Learning-based Prediction of Frailty in Elderly People with Digital Wearables : Data from the Berlin Aging Study II (BASE-II) [Poster presentation]. European Digital Medicine Conference Luxembourg 2022, Belval, Luxembourg.

Didier, J., de Landtsheer, S., Pires Pacheco, M. I., Kishk, A., Schneider, J., Demuth, I., & Sauter, T. (09 October 2022). Machine learning-based prediction of frailty in elderly people : Data from the Berlin Aging Study II (BASE-II) [Poster presentation]. 21st International Conference on Systems Biology, Berlin, Germany.

Badkas, A., de Landtsheer, S., & Sauter, T. (2022). Construction and contextualization approaches for protein-protein interaction networks. Computational and Structural Biotechnology Journal, 20, 3280-3290. doi:10.1016/j.csbj.2022.06.040
Peer Reviewed verified by ORBi

Machado, R. A. C., Stojevski, D., de Landtsheer, S., Lucarelli, P., Baron, A., Sauter, T., & Schaffner-Reckinger, E. (22 February 2021). L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness. Cell Communication and Signaling, 19 (22), 1-22. doi:10.21203/rs.3.rs-276404/v1
Peer Reviewed verified by ORBi

Badkas, A., Nguyen, T.-P., Caberlotto, L., Schneider, J., de Landtsheer, S., & Sauter, T. (2021). Degree Adjusted Large-Scale Network Analysis Reveals Novel Putative Metabolic Disease Genes. Biology, 10 (2). doi:10.3390/biology10020107
Peer reviewed

De Landtsheer, S. (2019). Optimization of logical networks for the modelling of cancer signalling pathways [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/39574

Cecchini, V. F., Nguyen, T.-P., Pfau, T., De Landtsheer, S., & Sauter, T. (2019). An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction. In V. F. Cecchini, An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction (1st ed, pp. 5). Da Nang, Vietnam: DA NANG PUBLISHING HOUSE.
Peer reviewed

Del Mistro, G., Lucarelli, P., Muller, I., De Landtsheer, S., Zinoveva, A., Hutt, M., Siegemund, M., Kontermann, R. E., Beissert, S., Sauter, T., & Kulms, D. (November 2018). Systemic network analysis identifies XIAP and IkappaBalpha as potential drug targets in TRAIL resistant BRAF mutated melanoma. NPJ Systems Biology and Applications, 4, 39. doi:10.1038/s41540-018-0075-y
Peer Reviewed verified by ORBi

Lucarelli, P., De Landtsheer, S., & Sauter, T. (2017). Systembasierte Analyse von Wirkstoffresistenzen bei Melanom. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/33864.

De Landtsheer, S., Trairatphisan, P., Lucarelli, P., & Sauter, T. (2017). FALCON: A Toolbox for the Fast Contextualisation of Logical Networks. Bioinformatics. doi:10.1093/bioinformatics/btx380
Peer reviewed

De Landtsheer, S. (2015). Near Full-Length Characterization and Population Dynamics of the Human Immunodeficiency Virus Type I Circulating Recombinant Form 42 (CRF42_BF) in Luxembourg. AIDS Research and Human Retroviruses. doi:10.1089/aid.2014.0364
Peer Reviewed verified by ORBi

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