Publications:

• M. Behr and A. Munk, Identifiability for blind source separation of multiple finite alphabet linear mixtures, IEEE Transactions on Information Theory, 63(9):5506-5517 (2017)
• M. Behr, C. Holmes, and A. Munk, Multiscale blind source separation, The Annals of Statistics, 46(2):711–744 (2018)
• M. Behr, Finite Alphabet Blind Separation, PhD thesis, University of Göttingen (2018)
• M. Behr, M. Azim Ansari, A. Munk, C. Holmes, Testing for dependence on tree structures, Proceedings of the National Academy of Sciences (PNAS) , 117(18):9787–9792 (2020)

• M. Pelizzola^*, M. Behr^*, H. Li, A. Munk, and A. Futschik, Multiple Haplotype Reconstruction from Allele Frequency Datan, Nature Computational Science, 1:262–271 (2021)

• L. Vanegas, M. Behr, and A. Munk, Multiscale Quantile Segmentation, Journal of the American Statistical Association, 117(539):1384–1397 (2022)

• M. Behr and A. Munk, Minimax estimation in linear models with unknown design over finite alphabets, SIAM Journal on Mathematics of Data Science, 4(2):490-513 (2022)

• M. Behr ^*, Y. Wang^*, X. Li, and B. Yu, Provable Boolean Interaction Recovery from Tree Ensemble obtained via Random Forests, Proceedings of the National Academy of Science (PNAS), 119(22):e2118636119 (2022)

• M. Behr , R. Burghaus, C. Diedrich, and J. Lippert, Opportunities and Challenges for AI-Based Analysis of RWD in Pharmaceutical R&D: A Practical Perspective, Künstliche Intelligenz, (2023)

Preprints:

• M. Behr ^*, K. Kumbier^*, A. Cordova-Palomera, M. Aguirre, E. Ashley, A. J. Butte, R. Arnaout, B. Brown, J. Priest, B. Yu, Learning epistatic polygenic phenotypes with Boolean interactions, bioRxiv preprint

• Q. Wang, T. M. Tang, N. Youlton, C. S. Weldy, A. M. Kenney, O. Ronen, J. W. Hughes, E. T. Chin, S. C. Sutton, A. Agarwal, X. Li, M. Behr , K. Kumbier, C. S. Moravec, W. H. W. Tang, K. B. Margulies, T. P. Cappola, A. J. Butte, R. Arnaout, J. B. Brown, J. R. Priest, V. N. Parikh, B. Yu, E. A. Ashley, Epistasis regulates genetic control of cardiac hypertrophy, medRxiv preprint

• M. Gorski, S. Wiegrebe, R. Burkhardt, M. Behr , H. Kuechenhoff, K. Stark, C. Boeger, I. Heid, Bias-corrected serum creatinine from UK Biobank electronic medical records generates an important data resource for kidney function trajectories, medRxiv preprint

Software:

• R-package slamR,http://www.stochastik.math.uni-goettingen.de/slamR
• R-package and Jupyter Notebook treeSeg,
  https://github.com/merlebehr/treeSeg
• R-package haploSep, (together with M. Pelizzola and H. Li)
  https://github.com/MartaPelizzola/haploSep
• R-package and Jupyter Notebook mqs, (together with L. Vanegas)
  https://github.com/ljvanegas/mqs
• GitHub repository epiTree, (together with K. Kumbier)
  https://github.com/merlebehr/epiTree

^* joint first author