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1
Content available remote Integrating Petri Nets and Flux Balance Methods in Computational Biology Models : a Methodological and Computational Practice
Pernice Simone, Follia Laura, Balbo Gianfranco, Milanesi Luciano, Sartini Giulia, Totis Niccoló, Lió Pietro, Merelli Ivan, Cordero Francesca, Beccuti Marco
Fundamenta Informaticae
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2020
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Vol. 171, nr 1-4
367--392
EN
Computational Biology is a fast-growing field that is enriched by different data-driven methodological approaches and by findings and applications in a broad range of biological areas. Fundamental to these approaches are the mathematical and computational models used to describe the different states at microscopic (for example a biochemical reaction), mesoscopic (the signalling effects at tissue level), and macroscopic levels (physiological and pathological effects) of biological processes. In this paper we address the problem of combining two powerful classes of methodologies: Flux Balance Analysis (FBA) methods which are now producing a revolution in biotechnology and medicine, and Petri Nets (PNs) which allow system generalisation and are central to various mathematical treatments, for example Ordinary Differential Equation (ODE) specification of the biosystem under study. While the former is limited to modelling metabolic networks, i.e. does not account for intermittent dynamical signalling events, the latter is hampered by the need for a large amount of metabolic data. A first result presented in this paper is the identification of three types of cross-talks between PNs and FBA methods and their dependencies on available data. We exemplify our insights with the analysis of a pancreatic cancer model. We discuss how our reasoning framework provides a biologically and mathematically grounded decision making setting for the integration of regulatory, signalling, and metabolic networks and greatly increases model interpretability and reusability. We discuss how the parameters of PN and FBA models can be tuned and combined together so to highlight the computational effort needed to perform this task. We conclude with speculations and suggestions on this new promising research direction.
2
Content available remote A Hybrid Petri Net Model of the Akt-Wnt-mTOR-p70S6K Signalling Network in Neurons
Fortin M. P., Hardy S. V.
Fundamenta Informaticae
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2018
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Vol. 160, nr 1/2
1--25
EN
Signalling networks in the mammalian cell are complex systems. Their dynamic properties can often be explained by the interaction of regulatory network motifs. Computational modelling is instrumental in explaining how these systems function. To accomplish this task in this paper, we combine hybrid Petri net modelling and simulation, which produce the individual trajectories of protein concentrations and enable structural analysis of the reaction network. In the end, we generate dynamic graphs to get a system view of the signalling network dynamics. We use this methodology on the regulatory network of the proteins mTOR and p70S6K. In neuronal synaptic plasticity, prolonged activation of these proteins is needed to support an increased protein synthesis. However, biologists wonder how two brief calcium influxes of 1 second each can lead to this long activation downstream. With our computational approach and a new model of the Akt-Wnt-mTOR-p70S6K network, we explore the current biological hypothesis for the response of mTOR: the crosstalk between the Akt and Wnt pathways. Simulation results indicate instead that a feedforward motif between Akt, GSK3 and TSC2 acts as a coincidence detector. From the simulation results, we can also make two predictions that can be tested experimentally and indicate where a molecular regulatory mechanism seems to be missing to completely explain the activity in the signalling network.
3
Content available remote G-MAPSEQ – a new method for mapping reads to a reference genome
Wojciechowski P., Frohmberg W., Kierzynka M., Zurkowski P., Blazewicz J.
Foundations of Computing and Decision Sciences
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2016
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Vol. 41, No. 2
123--142
EN
The problem of reads mapping to a reference genome is one of the most essential problems in modern computational biology. The most popular algorithms used to solve this problem are based on the Burrows-Wheeler transform and the FM-index. However, this causes some issues with highly mutated sequences due to a limited number of mutations allowed. G-MAPSEQ is a novel, hybrid algorithm combining two interesting methods: alignment-free sequence comparison and an ultra fast sequence alignment. The former is a fast heuristic algorithm which uses k-mer characteristics of nucleotide sequences to find potential mapping places. The latter is a very fast GPU implementation of sequence alignment used to verify the correctness of these mapping positions. The source code of G-MAPSEQ along with other bioinformatic software is available at: http://gpualign.cs.put.poznan.pl.
4
Content available Grafen – IPPT PAN computer of Biocentrum Ochota grid
Postek E., Kowalewski T. A.
IPPT Reports on Fundamental Technological Research
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2014
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nr 3
1--164
EN
The report treats on computing cluster in the IPPT. The first part of the report is a user manual of the cluster. In the following, we described chosen applications concerning applications of numerical methods in the computational biology, tectonophysics and fluid mechanics. Finally, we depicted a few selected computer programs that are implemented on the cluster.
PL
Praca traktuje o sposobie użytkowania klastra obliczeniowego znajdującego się w IPPT. Praca zawiera podręcznik użytkownika. W dalszym ciągu zostały opisane wybrane aplikacje dotyczące zastosowań metod numerycznych w problemach biologii obliczeniowej, tektonofizyki i mechaniki płynów. Na zakończenie podane zostały przykłady wybranych implementowanych programów komputerowych wraz z ich krótkimi opisami.
5
Content available remote Comparison of selected performances of biological and electronic information processing structures
Moškon M., Zimic N., Stražar M., Mraz M.
Przegląd Elektrotechniczny
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2013
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R. 89, nr 2a
166--169
EN
We present the information processing perspective on biological systems. Several metrics, similar to the ones used in digital electronic circuits, are introduced. These metrics allow us to compare biological information processing structures with their electronic counterparts, to define the ones with the best dynamical properties, analyse their compatibility and most importantly, automatize their design. Regarding the metric values obtained and used on a simple example, target applications of synthetic information processing biological structures are discussed.
PL
W artykule opisano zagadnienie przepływu informacji w systemach biologicznych. Zastosowano tu odwzorowanie na elementach i obwodach elektronicznych, co pozwoliło na analizę ich własności, w tym dynamicznych oraz zautomatyzowanie projektowania takich modeli. Zawarto także omówienie otrzymanych wyników badań.
6
Content available remote Accelerating molecular dynamics computing using iteration space slicing
Palkowski M.
Journal of Applied Computer Science
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2013
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Vol. 21, nr 2
85--96
EN
Molecular dynamics is an important computational tool to simulate and understand biochemical processes at the atomic level. Accurate modelling of processes such as simulation of the Newtonian equations of motion requires a large number of computation steps for systems with hundreds to millions of particles. In this paper, we present an approach to accelerate molecular dynamics simulations by means of automatic program loop parallelization. To parallelize code of applications, we have used the Iteration Space Slicing framework. The scope of the applicability of the approach is illustrated using the Gromacs package. Results of a performance analysis for parallelized loops executed on a multi-core computer are presented. The future work is discussed.
7
Content available remote Complexity Issues in Computational Biology
Blazewicz J., Kasprzak M.
Fundamenta Informaticae
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2012
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Vol. 118, nr 4
385-401
EN
The progress of research in the area of computational biology, visible in last decades, brought, among others, a new insight into the complexity issues. The latter, previously studied mainly on the ground of computer science or operational research, gained by a confrontation with problems from the new area. In the paper, several complexity issues inspired by computational biology are presented.
8
Content available remote Modeling Biology using Generic Reactive Animation
Setty Y., Cohen I.R., Harel D.
Fundamenta Informaticae
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2010
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Vol. 103, nr 1-4
235-246
EN
Complex biological systems involve incorporated behaviors of numerous processes, mechanisms and objects. However, experimental analysis, by its nature, divides biological systems into static interactions with little dynamics. To bridge the gap between experimental data and the underlying behavior, our group has been formalizing biological findings into mathematically and algorithmically rigorous specifications, which are then compiled into reactive models. To realistically animate our models, we designed a generic architecture for the earlier idea of reactive animation, in a way that allows it to link up reactive models with animation tools. Here, we describe the reactive animation approach and some of the benefits of employing it to simulate and analyze complex biological systems. We illustrate our approach with a model of pancreatic development, a highly complex system with a unique 3D structure, and also mention more recent work on adding animation to the generic cell project (GemCell).
9
Content available remote A Computer Scientist's Guide to the Regulatory Genome
Wilczyński B., Hvidste T.R.
Fundamenta Informaticae
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2010
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Vol. 103, nr 1-4
323-332
EN
Recent years have seen a wealth of computational methods applied to problems stemming from molecular biology. In particular, with the completion of many new full genome sequences, great advances have been made in studying the role of non-protein-coding parts of the genome, reshaping our understanding of the role of DNA sequences. Recent breakthroughs in experimental technologies allowing us to inspect the innards of cells on a genomic scale has provided us with unprecedented amounts of data, posing new computational challenges for scientists working to uncover the secrets of life. Due to the binary-like nature of the DNA code and switch-like behavior of many regulatory mechanisms, many of the questions that are currently in focus in biology are surprisingly related to problems that have been of long-term interest to computer scientists. In this review, we present a glimpse into the current state of research in computational methods applied to modeling the regulatory genome. Our aim is to cover current approaches to selected problems from molecular biology that we consider most interesting from the perspective of computer scientists as well as highlight new challenges that will most likely draw the attention of computational biologists in the coming years.
10
Content available remote Resolving power of isothermic DNA sequencing chips
Formanowicz P.
Bulletin of the Polish Academy of Sciences. Technical Sciences
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2004
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Vol. 52, nr 3
231-237
EN
DNA sequencing remains one of the most important problems in molecular and computational biology. One of the methods used for this purpose is sequencing by hybridization. In this approach usually DNA chips composed of a flul library of oligonucleotides of a given length are used, but in principle it is possible to use another types of chips. Isothermic DNA chips, being one of them, when used for sequencing may reduce hybridization error rate. However, it was not clear if a number of errors following from subsequence repetitions is also reduced in this case. In this paper a method for estimating resolving power of isothermic DNA chips is described which allows for a comparison of such chips and the classical ones. The analysis of the resolving power shows that the probability of sequencing errors caused by subsequence repetitions is greater in the case of isothermic chips in comparison to their classical counterparts of a similar cardinality. This result suggests that isothermic chips should be chosen carefully since in some cases they may not give better results than the classical ones.
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