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Projects / Programmes source: ARIS

Mathematical and computational methods for polyhedral self-assembly

Research activity

Code Science Field Subfield
1.07.01  Natural sciences and mathematics  Computer intensive methods and applications  Algorithms 

Code Science Field
1.01  Natural Sciences  Mathematics 
Keywords
nanostructure design, self-assembly, polypeptides, polyhedra, symmetry, protein, synthetic biology, coiled-coil, strong trace, topofold, origami, algorithms, modeling, software, topological graph theory, flag graphs, parallel computing, plane tilings
Evaluation (rules)
source: COBISS
Researchers (11)
no. Code Name and surname Research area Role Period No. of publicationsNo. of publications
1.  34561  PhD Nino Bašić  Mathematics  Head  2020 - 2023 
2.  01467  PhD Vladimir Batagelj  Mathematics  Researcher  2020 - 2023 
3.  04967  PhD Andrej Brodnik  Computer intensive methods and applications  Researcher  2020 - 2023 
4.  06628  PhD Roman Jerala  Biochemistry and molecular biology  Researcher  2020 - 2023 
5.  24997  PhD Klavdija Kutnar  Mathematics  Researcher  2020 - 2023 
6.  37987  PhD Fabio Lapenta  Biochemistry and molecular biology  Researcher  2020 
7.  53353  Klemen Mezgec  Biochemistry and molecular biology  Researcher  2020 - 2023 
8.  01941  PhD Tomaž Pisanski  Mathematics  Researcher  2020 - 2023 
9.  36549  PhD Jernej Rus  Mathematics  Researcher  2020 - 2023 
10.  38337  PhD Žiga Strmšek  Biochemistry and molecular biology  Researcher  2021 - 2022 
11.  23555  PhD Jernej Vičič  Computer science and informatics  Researcher  2020 - 2023 
Organisations (3)
no. Code Research organisation City Registration number No. of publicationsNo. of publications
1.  2790  University of Primorska, Faculty of mathematics, Natural Sciences and Information Technologies  Koper  1810014009 
2.  0104  National Institute of Chemistry  Ljubljana  5051592000  10 
3.  2975  ABELIUM d.o.o., research and development  Ljubljana  3557952 
Abstract
The main goal of this project is to further develop existing mathematical models for self-assembly of nanostructures and also create new ones. In particular, we will make heavy use of flag graphs and results from topological graph theory to produce those models. A stronger link between topological graph theory and synthetic biology will be established. All this will be implemented in the form of a user-friendly well-documented library for Python and/or SageMath, which will enable researchers to do various "in silico" experiments. New data structures and algorithms will be developed and incorporated in this software library. This software library will be used to solve several practical self-assembly problems in synthetic biology to demonstrate its usability. Parallelisable algorithms will be developed to enable (computationally intensive) enumerations of strong traces of large polyhedra on multiprocessor systems and computer clusters, which was not possible so far. We will also consider self-assembly of planar nanostructures from the viewpoint of mathematical theory of tilings. The mathematics and software that will be developed will have direct applications in the area of synthetic biology.
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