Computational Biomodelling Laboratory
|Leader Dr. Ion Petre|
The research of the laboratory centers on the computational modelling of biochemical systems. The approach is to understand as computations the myriad of biochemical processes that evolve in parallel, influence each other, propagate signals, or cooperate on various tasks. Our goal is to increase the understanding of how entire cells adapt, communicate, and survive in dynamic environments, all in terms of computations. Having sound computational models for a biochemical system allows one to employ formal reasoning about its pathways or regulatory networks, formulating predictions and/or running simulations. Such models are also useful for designing novel sorts of computations based on the principles that underline the functioning of bio-systems. Our group is leading research on computational bio-processes, including computational processes in living cells, as well as nature-inspired human-designed computations. The general interest of the laboratory is gaining an understanding of fundamental structures behind the functioning of all kinds of bio-systems. We have considerable expertise in building discrete models, based on combinatorics, graph theory, stochastic processes, etc.
- Computational models for basic cellular processes
- Models for self-assembly and applications to nanotechnology
- Regulatory networks
- Signaling pathways
- Computer-based simulators for bio-systems
- Nature-inspired computational paradigms
Computing at nano-scale
Academy of Finland, 2005-2010
Nanotechnology (manipulating matter at the atomic scale) gets its name from the measurement unit of nanometer (a billionth of a meter), the width of about 4 individual atoms. Being able to manipulate single atoms, one can create in principle new materials with very special properties: smaller, stronger, tougher, lighter, or more resilient than anything ever made.
Self-assembly lies at the heart of nanotechnology. Molecular self-assembly is a strategy for nano-fabrication that involves designing a number of entities that, when placed together, will self-aggregate into desired structures. Self-assembly is nothing new: it is used all the time in biology for the development of complex, functional structures. Self-assembly has many advantages: it eliminates the difficulty of direct atomic-level manipulation of structure, it draws from the huge number of examples in biology and biochemistry for inspiration, and it tends to produce relatively defect-free and ``self-healing'' structures since it requires that the target structures are thermodynamically the most stable ones.
We investigate mathematical models for self-assembly, contributing to laying solid foundations for nano-science, that are still missing to a large extent at this time. Based on such foundations, we seek to clarify several central questions: e.g., what can be effectively self-assembled (and thus nano-fabricated), how complex is it to self-assemble a given shape, or what initial structures can self-assemble into a certain shape.
Computational processes in living cells (COMPROC)
Academy of Finland, 2004-2007, within the research program for Systems Biology and Bioinformatics.
Ciliates are an ancient group of organisms (about 2.5 billion years old), often classified as the most complex unicellular organisms on Earth. This family includes the fastest living form on Earth (Strombidium), as well as some unicellular organisms with digestive systems almost as complex as ours (Paramecium). A phenomenon unique to ciliates is the presence of two kinds of functional nuclei in the same cell: a micronucleus and a macronucleus. The macronucleus is the household nucleus that provides the RNA transcripts for producing proteins, while the micronucleus is activated only in the process of sexual reproduction, where at some stage the genome of the micronucleus gets transformed into the genome of the macronucleus in the process called gene assembly - this is the most involved process of DNA manipulation known in Nature !
The process of gene assembly has the attention of the Biocomputing community for several years already. It is by now clear that the process of gene assembly in ciliates is highly computational: it turns out that ciliates "know" one of the basic data structures of Computer Science - the linked list - and use it in a very elegant pattern matching manner in the process of gene assembly! We are investigating a set of three molecular operations that accomplishes the gene assembly through the "fold and recombine" paradigm. We introduced the mathematical model of pointer reduction systems to formalize the micronuclear gene patterns (through permutations, strings and graphs) and the gene assembly process. Our investigation of these systems resulted in a uniform explanation of all known experimental results concerning gene assembly in ciliates.
Molecular Computing Network (MolCoNet)
In cooperation with Professor Tero Harju, University of Turku, and other 14 European groups. European Union IST FWP5, 2002-2004.
Molecular computing is a novel, exciting and a genuinely interdisciplinary research area which lies at the boundary of Computer Science and Molecular Biology. An important advantage offered by computations with bio-molecules is the massive parallelism: the number of operations that can be executed at the same time is proportional to the number of molecules involved, which is of the order of 10 to the power 19 . Also, operations which involve bio-molecules are over a billion times more energy efficient with respect to electronic chips, and the information can be stored at a density of about a billion times higher than in usual electronic computers. The major applications to massively-parallel molecular computation range from novel computer architectures in conventional hardware and novel algorithmic solutions to difficult problems to self-assembling technology and intelligent nano-scale construction. The theoretical studies involve the investigation of new computational models based on paradigms coming from bio-chemistry: the complementarity of the two strands of a DNA molecule, the signaling within and between cells, or the structural organization of cells.
A computational model for eukaryotic heat-shock response
In cooperation with the Software Construction laboratory of TUCS (Academy Professor Ralph Back) and Turku Centre for Biotechnology (Academy Professor Lea Sistonen and Professor John Eriksson)
The heat shock response is the answer of the eukaryotic cell to exposure to extreme conditions that cause acute or chronic stress. It is characterized by increased expression of heat shock proteins (HSPs) that function as molecular chaperones in regulating the misfolded proteins. The enhanced heat shock gene expression is regulated by heat shock transcription factors (HSFs), that are in turn downregulated by HSP. We are building a discrete model for the eukaryotic heat-shock response that tracks the main actors of the process (HSP, HSF and others) and their interactions in terms of computations. The model is also supported by a computer-based simulator.
You can find us in the ICT-building, Joukahaisenkatu 3-5 A, 5th floor, FIN-20520 Turku, Finland.
People involved in the laboratory:
- Ralph-Johan Back, Åbo Akademi University, Department of Information Technologies
- Andrzej Mizera, Åbo Akademi University, Department of Information Technologies
- Ion Petre, Åbo Akademi University, Department of Information Technologies
- Vladimir Rogojin, Åbo Akademi University, Department of Information Technologies
- Ishdorj Tseren-Onolt, Åbo Akademi University, Department of Information Technologies
- Tero Harju, University of Turku, Department of Mathematics
Alhazov, Artiom and Petre, Ion and Rogojin, Vladimir:
The Parallel Complexity of Signed Graphs: Decidability and an Improved Algorithm
Theoretical Computer Science, 2009
Alhazov, Artiom and Li, Chang and Petre, Ion:
Computing the Graph-Based Parallel Complexity of Gene Assembly
Theoretical Computer Science, Volume to appear, 2009
Petre, Ion and Salomaa, Arto:
Algebraic Systems and Pushdown Automata
Petre, Ion and Mizera, Andrzej and Hyder, Claire and Mikhailov, Andrey and Eriksson, John and Sistonen, Lea and Back, Ralph-Johan:
A New Mathematical Model for the Heat Shock Response
TUCS General Series, Number 47, 2008
Petre, Ion and Rogojin, Vladimir:
Decision Problems for Shuffled Genes
Information and Computation, Volume 206, Number 11, 2008
Harju, Tero and Petre, Ion and Rogojin, Vladimir and Rozenberg, Grzegorz:
Patterns of Simple Gene Assembly
Discrete applied mathematics, Volume 156, Number 14, 2008
Alhazov, Artiom and Petre, Ion and Rogojin, Vladimir:
Solutions to Computational Problems Through Gene Assembly
Natural computing, Volume 7, Number 3, 2008
Back, Ralph-Johan and Ishdorj, Tseren-Onolt and Petre, Ion:
A Petri-net formalization of the heat shock response model
Chen, Haiming and Ionescu, Mihai and Ishdorj, Tseren-Onolt and Paun, Andrei and Paun, Gheorghe and Pérez-Jiménez, Mario J.:
Spiking Neural P Systems with Extended Rules: Universality and Languages
Natural Computing,, Volume 7, Number 2, 2008
Ishdorj, Tseren-Onolt and Leporati, Alberto:
Uniform Solutions to SAT and 3-SAT by Spiking Neural P Systems with Pre-computed Resources
Natural Computing, Volume 7, Number 4, 2008