PROBRAL
Mesoscopic Molecular Dynamics Simulations
Development of Models and Computational Strategies for Complex Structural Bioinformatics Problems
There is a wide range of unanswered scientific questions which cannot be answered neither by experiments nor by classical modeling and simulation approaches. One question is how to consider microscopic and macroscopic effects in one model. On the one hand, available microscopic approaches (Molecular Dynamics (MD) type) are precise but computational too complex for large or multi-scale problems. On the other hand, several macroscopic methods (Computational Fluid Dynamics (CFD) type) cannot show crucial microscopic effects. Therefore, a mesoscopic scale model is required that closes this gap. For such a Mesoscopic Molecular Dynamics (MMD) model, we propose to take advantage of the Lattice Boltzmann Method (LBM), a modern CFD method, and state-of-the-art MD methods in order to combine both. This MMD model resolves certain microscopic effects important for the considered macroscopic application. In this project, two complementary academic expert groups from Brazil and Germany join together in order to provide an interdisciplinary research and academic education in the fields of mathematics, computer science, biology, chemistry and engineering to PhD students as well as to researchers.
Researchers
- Dr. Hugo Verli CBiot/UFRGS
- Dr. Ana Lúcia Cetertich Bazzan PPGC/INF/UFRGS
- Dr. Rodrigo Ligabue Braun DF/UFCSPA
- Dr. Bruno César Feltes PPGC/INF/UFRGS
- Dr. Gudrun Thäter IANM/KIT
- Dr. Hermann Nirschl IANM/KIT
- Dr. Manuel Riveros Escalona PPGC/INF/UFRGS
Graduate Students/Collaborators
Study Missions
Work Missions
PROBRAL Workshops
2019 - Workshop Lattice Boltzmann Methods with OpenLB Software Lab
Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil
On December 10 and 11, 2019, we held the workshop "Lattice Boltzmann Methods with OpenLB Software Lab" at the Instituto de Informática from the UFRGS. The workshop was organized by the Structural Bioinformatics and Computational Biology Lab (SBCBLAB/INF/UFRGS - Brazil) and the Lattice Boltzmann Research Group (LBRG/IANM//KIT - Germany). We were happy to host 35 participants, including five speakers from LBRG (KIT, Karlsruhe, Germany).
PROBRAL Meetings / Presentations
2019 - First Meeting
1st Presentation of Brazilian research to the LBRG
Objective: In this meeting of the Lattice Boltzmann Research Group from KIT, the Ph.D. Candidate Bruno Iochins Grisci presented his current work to the German researchers.2nd Presentation of Brazilian research to the LBRG
Objective: In this meeting of the Lattice Boltzmann Research Group from KIT, the Ph.D. Candidate Pedro Henrique Narloch presented his current work to the German researchers.2019 - Second meeting
2019 - Third meeting
2021 - Fourth Meeting
2021 - Fifth Meeting
Participation in Events
International workshop on data-driven modeling and optimization in fluid mechanics
This workshop showcased the application of machine learning, evolutionary algorithms, and adjoint-based optimization to fluid dynamics-related problems with special focus on turbulent flows and flow control
7th Heidelberg Laureate Forum
The Ph.D. Candidate Bruno Iochins Grisci was among the 200 young math and Computer Science researchers worldwide invited to attend the Heidelberg Laureate Forum. The event brings together the young researchers with winners of the Abel Award and Field Medalist (math), ACM AM Turing Award and ACM Computing (Computer Science) Award and Nevanlinna Award (Information Science) in Heidelberg, Germany. The focus of the forum is to promote and advance research in these areas, but also to enable contact and exchange of experiences between researchers. For example, the event can balance technical lectures, workshops, and visits to research institutions and local businesses with social activities, dinners, and discussions geared toward interaction among participants. Bruno Grisci was also invited to present his current research, titled "Ranking Relevances from Neural Networks for the Selection of Biological Features.
Photos | Presentation Video
International Days "Karlsruhe and the World
Organized by the International Affairs Business Unit (INTL), the International Days offered an extensive program of presentations and workshops, cultural contributions, and an exhibition. The program also covered presentations on international scientific and international activities and relations of KIT, as well as the Humboldt-Lightning-Talks, in which Humboldt fellows presented their current research.
The 19th IEEE International Conference on Bioinformatics and BioEngineering
Pedro had a paper published in the 19th annual IEEE International Conference on Bioinformatics and Bioengineering (BIBE). BIBE aims at building synergy between Bioinformatics and Bioengineering/Biomedical, two complementary disciplines that hold great promise for the advancement of research and development in complex medical and biological systems, agriculture, environment, public health, drug design.
X-Meeting 2019 - Dissertation Award
The Ph.D. Candidate Bruno Iochins Grisci was invited to remotely present his Master Dissertation in the category “Dissertation Award” on the X-Meeting 2019. The work, titled "N3O: A NEAT expansion for improving classification and feature selection applied to microarray data", was featured in the top 3 best dissertation in Bioinformatics by the Associação Brasileira de Bioinformática e Biologia Computacional (AB3C).
21st EMBL PhD Symposium: Facing the Future: Challenges and Perspectives in Life Sciences in the 21st Century
The Ph.D, Candidate Bruno Iochins Grisci was among the participants of the PhD Symposium, organized by the European Molecular Biology Laboratory. The event discusses environmental and global health issues, highlight interdisciplinary approaches as physics and informatics in biology, present innovations in life sciences and raise awareness of the challenges within the scientific community including big data, open access and gender equality. Bruno Grisci was also invited to present his current research, titled "Selection of Biological Features by Ranking the Relevances of Neural Networks Inputs".
MathSEE course on Machine Learning
The Ph.D, Candidate Bruno Iochins Grisci was among the participants of the MathSEE course of Machine Learning.
Publications
- Rosetta Ligand-Protein Docking with Self-Adaptive Differential Evolution NARLOCH, P. H.; DORN, M. 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE), p. 23-30, 2019.
- Ranking Relevances from Neural Networks for the Selection of Biological Features GRISCI, B. I.; KRAUSE, M. J.; DORN, M. 7th Heidelberg Laureate Forum, 2019.
- Selection of Biological Features by Ranking the Relevances of Neural Networks Inputs GRISCI, B. I.; KRAUSE, M. J.; DORN, M. 21st EMBL PhD Symposium, 2019.
- Evaluation of drug repositioning by molecular docking of pharmaceutical resources available in the Brazilian healthcare system against SARS-CoV-2 GRAHL, M. V. C.; ALCARÁ, A. L.; PERIN, A. P. A.; MORO, C. F.; PINTO, E. S. M.; FELTES, B. C.; GHILARDI, I. M.; RODRIGUES, F. V. F.; DORN, M.; COSTA, J. C.; SOUZE, O. N.; LIGABUE-BRAUN, R. Informatics in Medicine Unlocked, v. 23, p. 100539, 2021.
- Genetic and molecular Omp25 analyses from worldwide Brucella canis strains: Possible mutational influences in protein function LOPES, C. E.; DE CARLI, S.; FELTES, B. C.; PINTO, E. S. M.; SALA, R. D. V.; DORN, M.; SIQUEIRA, F. M. Gene, v. 817, p. 146175, 2022.
- Modifying the catalytic preference of alpha-amylase toward n-alkanes for bioremediation purposes using in silico strategies PINTO, E. S. M.; FELTES. B. C.; PEDEBOS, C.; DORN, M. Journal of Computational Chemistry, v. 42, p. 1540-1551, 2021.
- A Study on Shape-Dependent Settling of Single Particles with Equal Volume Using Surface Resolved Simulations TRUNK, R.; BRETL, C.; THÄTER, G.; NIRSCHL, H.; DORN, M.; KRAUSE, M. J. Computation, v. 9, p. 1-35, 2021.
- Relevance aggregation for neural networks interpretability and knowledge discovery on tabular data GRISCI, B. I.; KRAUSE, M. J.; DORN, M. Information Sciences, v. 559, p. 111-129, 2021.
- Solving fluid flow domain identification problems with adjoint lattice Boltzmann methods KLEMENS, F.; FÖRSTER, B.; DORN, M.; THÄTER, G.; KRAUSE, M. J. Computers & Mathematics with Applications, v. 79, p. 17-33, 2020.
- Preliminary Study of Particle Settling Behaviour by Shape Parameters via Lattice Boltzmann Simulations BRETL, C.; TRUNK, R.; NIRSCHL, H.; THÄTER, G; DORN, M.; KRAUSE, M. J. High Performance Computing in Science and Engineering, 2021.
- ConfID: an analytical method for conformational characterization of small molecules using molecular dynamics trajectories POLÊTO, M. D.; GRISCI, B. I.; DORN, M.; VERLI, H. Bioinformatics, v. 36, p. 3576-3577, 2020.
- Differential Evolution Multi-Objective for Tertiary Protein Structure Prediction NARLOCH, P. H.; DORN, M. Applications of Evolutionary Computation, v. 12104, p. 165-180, 2020.