Peer-reviewed Journal Papers

  • S. K. Sieberts, J. Schaff, M. Duda, B. Á. Pataki, M. Sun, P. Snyder, J.-F. Daneault, F. Parisi, G. Costante, U. Rubin, P. Banda, Y. Chae, E. Chaibub Neto, R. Dorsey, Z. Aydın, A. Chen, L. L. Elo, C. Espino, E. Glaab, E. Goan, F. N. Golabchi, Y. Görmez, M. K. Jaakkola, J. Jonnagaddala, R. KLÉ, D. Li, C. McDaniel, D. Perrin, N. M. Rad, E. Rainaldi, S. Sapienza, P. Schwab, N. Shokhirev, M. S. Venäläinen, G. Vergara-Diaz, Y. Zhang, Y. Wang, Y. Guan, D. Brunner, P. Bonato, L. M. Mangravite, L. Omberg, Parkinson’s Disease Digital Biomarker Challenge Consortium. Crowdsourcing digital health measures to predict Parkinson’s disease severity: the Parkinson’s Disease Digital Biomarker DREAM Challenge. Nature Digital Medicine, 4 (53), 2021, doi, free download, bioarxiv
  • T. Bergquist, T. Schaffter, Y. Yan, T. Yu, J. Prosser, J. Gao, G. Chen, Ł. Charzewski, Z. Nawalany, I. Brugere, R. Retkute, A. Prusokas, A. Prusokas, Y. Choi, S. Lee, J. Choe, I. Lee, S. Kim, J. Kang, Patient Mortality Prediction DREAM Challenge Consortium, Sean D. Mooney. Evaluation of crowdsourced mortality prediction models as a framework for assessing AI in medicine. 2021, medrxiv
  • J. Bürger, V. Picanço Rodrigues, R. Cassel, C. Mejía Argueta, and P. Banda. Data-Driven & Model-Driven Methods for Supply Chain Risk Management: A Comprehensive Framework. (under review) 2021
  • J. Tanevski, T. Nguyen, B. Truong, N. Karaiskos, M. E. Ahsen, X. Zhang, C. Shu, Y. Hu, H. VV Pham, X. Li, T. D. Le, A. Tarca, G. Bhatti, R. Romero, N. Karathanasis, P. Loher, Y. Chen, Z. Ouyang, D. Mao, Y. Zhang, M. Zand, J. Ruan, C. Hafemeister, P. Qiu, D. Tran, T. Nguyen, A. Gabor, T. Yu, E. Glaab, R. Krause, P. Banda, G. Stolovitzky, N. Rajewsky, J. Saez-Rodriguez, P. Meyer, and DREAM SCTC Consortium. Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data. Life Science Alliance, 3(11), 2020, doi, free download, bioarxiv
  • F. Baldini, J. Hertel, E. Sandt, C. Thinnes, L. Neuberger-Castillo, L. Pavelka, F. Betsou, R. Krüger, I. Thiele, and NCER-PD Consortium. Parkinson’s disease-associated alterations of the gut microbiome predict disease-relevant changes in metabolic functions. BMC Biology, 18(62), 2020, doi, free download
  • D. R. Bobbili, P. Banda, R. Krüger, and P. May. Excess of singleton loss-of-function variants in Parkinson’s disease contributes to genetic risk. Journal of Medical Genetics, 2020, doi
  • P. Banda, J. Caughman, M. Cenek, and C. Teuscher. Shift-symmetric Configurations in Two-dimensional Cellular Automata: Irreversibility, Insolvability, and Enumeration. Chaos: An Interdisciplinary Journal of Nonlinear Science, 29(6), 063120, 2019, doi, arxiv
  • G. Hipp, M. Vaillant, N. J. Diederich, K. Roomp, V. P. Satagopam, P. Banda, E. Sandt, K. Mommaerts, S. K. Schmitz, L. Longhino, A. Schweicher, A.-M. Hanff, B. Nicolai, P. Kolber, D. Reiter, L. Pavelka, S. Binck, C. Pauly, L. Geffers, F. Betsou, M. Gantenbein, J. Klucken, T. Gasser, M. T. Hu, R. Balling, and R. Krüger. The Luxembourg Parkinson’s Study: A Comprehensive Approach for Stratification and Early Diagnosis. Frontiers in Aging Neuroscience, 10, 326, 2018, doi, free download
  • S. Herzinger, V. Grouès, W. Gu, V. Satagopam, P. Banda, C. Trefois, and R. Schneider. Fractalis: A Scalable Open-source Service for Platform-independent Interactive Visual Analysis of Biomedical Data. GigaScience, 7(9), Oxford University Press, 2018, doi, free download
  • D. Blount, P. Banda, C. Teuscher, and D. Stefanovic. Feedforward Chemical Neural Network: An In Silico Chemical System That Learns XOR. Journal of Artificial Life, MIT Press, 23(3), 295-317, 2017, doi
  • P. Banda, C. Teuscher. COEL: A Cloud-Based Reaction Network Simulator. Frontiers in Robotics and AI, 3(13), 2016, doi
  • J. Moles, P. Banda, and C. Teuscher. Delay Line as a Chemical Reaction Network. Parallel Processing Letters, 21(1), 2015, doi, arxiv
  • P. Banda, J. Caughman, and J. Pospichal. Configuration Symmetry and Performance Upper Bound of One-Dimensional Cellular Automata for the Leader Election Problem. Journal of Cellular Automata, 10(1-2), 1-21, 2015
  • P. Banda, C. Teuscher, and D. Stefanovic. Training an Asymmetric Signal Perceptron through Reinforcements in an Artificial Chemistry. Journal of the Royal Society, Interface, 11(93), 2014, doi
  • P. Banda, C. Teuscher, and M. R. Lakin. Online Learning in a Chemical Perceptron. Journal of Artificial Life, MIT Press, 19(2), 2013, doi, free download

Peer-reviewed Conference Papers

  • H. Nguyen, P. Banda, D. Stefanovic, and C. Teuscher. Reservoir Computing with Random Chemical Systems. Proceedings of The 2020 Conference on Artificial Life, MIT Press, 491-499, 2020, doi
  • J. Daneault, G. Vergara-Diaz, G. Costante, E. Fabara, G. Ferreira-Carvalho, F. Golabchi, F. Parisi, S. Sapienza, Y. Chae, P. Snyder, P. Aubin, P. Banda, D. Brunner, R. Dorsey, L. Mangravite, W. Marks, E. Neto, U. Rubin, E. Soderberg, D. Daeschler, S. Moore, S. Sieberts, L. Omberg, and P. Bonato. The Levodopa Response Trial and the Parkinson Disease Digital Biomarker Challenge: Monitoring symptoms of Parkinson’s disease in the lab and home using wearable sensors (abstract). The 2018 International Congress of Parkinson’s Disease and Movement Disorders. Movement Disorders : Official Journal of the Movement Disorder Society, 33(S2), 525, 2018, doi
  • P. Banda, and C. Teuscher. An Analog Chemical Circuit with Parallel-Accessible Delay Line for Learning Temporal Tasks. In Sayama, H., et al. eds.: ALIFE 14: Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems, MIT Press, 482-489, 2014, doi, free download
  • P. Banda, D. Blount, and C. Teuscher. COEL: A Web-based Chemistry Simulation Framework. In Stepney, S., Andrews, P. eds.: CoSMoS 2014: Proceedings of the 7th Workshop on Complex Systems Modelling and Simulation, Luniver Press, 35-60, 2014, arxiv
  • P. Banda, and C. Teuscher. Learning Two-input Linear and Nonlinear Analog Functions with a Simple Chemical System. In Ibarra, O.H., et al. eds.: Unconventional Computing and Natural Computing Conference, Volume 8553 of Lecture Notes in Computer Science. Springer International Publishing Switzerland, 14-26, 2014, doi, arxiv
  • P. Banda, and C. Teuscher. Complex Dynamics in Random DNA Strand Circuits (extended abstract). The 19th International Conference on DNA Computing and Molecular Programming, 2013
  • P. Banda. Cellular Automata Evolution Of Leader Election. In Kampis, G., Karsai, I., Szathmáry, E., eds.: Advances in Artificial Life. Darwin Meets von Neumann. Volume 5778 of Lecture Notes in Computer Science. Springer Berlin / Heidelberg, 310-317, 2011, doi
  • P. Banda. Symmetry Breaking and Limits of Self-stabilization in Cellular Automata for the Leader Election Problem (in Slovak). Kelemen, J., Kvasnicka, V., eds.: Cognition and Artificial Life ’10, SLU Opava, 37-42, 2010
  • P. Banda. Computational Mechanics, Evolution of Cellular Automata and Leader Election Problem (in Slovak). Kelemen, J., Kvasnicka, V., Rybar, J., eds.: Cognition and Artificial Life ’09, SLU Opava, 2009
  • P. Banda. Upper Bound Performance of Cellular Automata for the Leader Election Problem in Arbitrary Ring. Proceedings in Informatics and Information Technologies, IIT.SRC 2009 – Student Research Conference, 158-165, 2009
  • P. Banda. Cellular Automata Evolution and Leader Election in a Symmetric Ring. Proceedings in Informatics and Information Technologies, IIT.SRC 2008 – Student Research Conference, 303-310, 2008


  • P. Banda. Novel Methods for Learning and Adaptation in Chemical Reaction Networks. Dissertation, Portland State University, 2015, free download
  • P. Banda. Anonymous Leader Election in One- and Two-Dimensional Cellular Automata. Dissertation, Comenius University, 2014, free download
  • P. Banda. Binary Cellular Automata Approach to Anonymous, Self-Stabilizing Leader Election on Rings. Rigorous Thesis, Comenius University, 2010
  • P. Banda. Cellular Automata Evolution, Computational Mechanics and Global Coordination (in Slovak). Master’s Thesis, Comenius University, 2006


  • A. Goudarzi, S. Marzen, P. Banda, G. Feldman, C. Teuscher, and D. Stefanovic. Memory and information processing in recurrent neural networks. 2016, arxiv
  • A. Goudarzi, P. Banda, M. R. Lakin, C. Teuscher, and D. Stefanovic. A Comparative Study of Reservoir Computing for Temporal Signal Processing. 2014, arxiv