391 research outputs found

    Modelling epistasis in genetic disease using Petri nets, evolutionary computation and frequent itemset mining

    Get PDF
    Petri nets are useful for mathematically modelling disease-causing genetic epistasis. A Petri net model of an interaction has the potential to lead to biological insight into the cause of a genetic disease. However, defining a Petri net by hand for a particular interaction is extremely difficult because of the sheer complexity of the problem and degrees of freedom inherent in a Petri net’s architecture. We propose therefore a novel method, based on evolutionary computation and data mining, for automatically constructing Petri net models of non-linear gene interactions. The method comprises two main steps. Firstly, an initial partial Petri net is set up with several repeated sub-nets that model individual genes and a set of constraints, comprising relevant common sense and biological knowledge, is also defined. These constraints characterise the class of Petri nets that are desired. Secondly, this initial Petri net structure and the constraints are used as the input to a genetic algorithm. The genetic algorithm searches for a Petri net architecture that is both a superset of the initial net, and also conforms to all of the given constraints. The genetic algorithm evaluation function that we employ gives equal weighting to both the accuracy of the net and also its parsimony. We demonstrate our method using an epistatic model related to the presence of digital ulcers in systemic sclerosis patients that was recently reported in the literature. Our results show that although individual “perfect” Petri nets can frequently be discovered for this interaction, the true value of this approach lies in generating many different perfect nets, and applying data mining techniques to them in order to elucidate common and statistically significant patterns of interaction

    metaSHARK: software for automated metabolic network prediction from DNA sequence and its application to the genomes of Plasmodium falciparum and Eimeria tenella

    Get PDF
    The metabolic SearcH And Reconstruction Kit (metaSHARK) is a new fully automated software package for the detection of enzyme-encoding genes within unannotated genome data and their visualization in the context of the surrounding metabolic network. The gene detection package (SHARKhunt) runs on a Linux systemand requires only a set of raw DNA sequences (genomic, expressed sequence tag and/ or genome survey sequence) as input. Its output may be uploaded to our web-based visualization tool (SHARKview) for exploring and comparing data from different organisms. We first demonstrate the utility of the software by comparing its results for the raw Plasmodium falciparum genome with the manual annotations available at the PlasmoDB and PlasmoCyc websites. We then apply SHARKhunt to the unannotated genome sequences of the coccidian parasite Eimeria tenella and observe that, at an E-value cut-off of 10(-20), our software makes 142 additional assertions of enzymatic function compared with a recent annotation package working with translated open reading frame sequences. The ability of the software to cope with low levels of sequence coverage is investigated by analyzing assemblies of the E.tenella genome at estimated coverages from 0.5x to 7.5x. Lastly, as an example of how metaSHARK can be used to evaluate the genomic evidence for specific metabolic pathways, we present a study of coenzyme A biosynthesis in P.falciparum and E.tenella

    Automatic Parameterization of the Purine Metabolism Pathway through Discrete Event-based Simulation

    Get PDF
    Model development and analysis of metabolic networks is recognized as a key requirement for integrating in-vitro and in-vivo experimental data. In-silico simulation of a biochemical model allows one to test different experimental conditions, helping in the discovery of the dynamics that regulate the system. Although qualitative characterizations of such complex mechanisms are, at least partially, available, a fully-parametrized quantitative description is often miss- ing. On the other hand, several characteristics and issues to model biological systems are common to the electronics system modelling, such as concurrency, reactivity, abstraction levels, automatic reverse engineering, as well as design space explosion during validation. This work presents a methodology that applies languages, techniques, and tools well established in the context of electronic design automation (EDA) for modelling and simulation of metabolic networks through Petri nets. The paper presents the results obtained by applying the proposed methodology to model the purine metabolism starting from the metabolomics data obtained from naive lymphocytes and autoreactive T cells implicated in the induction of experimental autoimmune disorders

    Computational models for inferring biochemical networks

    Get PDF
    Biochemical networks are of great practical importance. The interaction of biological compounds in cells has been enforced to a proper understanding by the numerous bioinformatics projects, which contributed to a vast amount of biological information. The construction of biochemical systems (systems of chemical reactions), which include both topology and kinetic constants of the chemical reactions, is NP-hard and is a well-studied system biology problem. In this paper, we propose a hybrid architecture, which combines genetic programming and simulated annealing in order to generate and optimize both the topology (the network) and the reaction rates of a biochemical system. Simulations and analysis of an artificial model and three real models (two models and the noisy version of one of them) show promising results for the proposed method.The Romanian National Authority for Scientific Research, CNDI–UEFISCDI, Project No. PN-II-PT-PCCA-2011-3.2-0917

    Practical Use of High-level Petri Nets

    Get PDF
    This booklet contains the proceedings of the Workshop on Practical Use of High-level Petri Nets, June 27, 2000. The workshop is part of the 21st International Conference on Application and Theory of Petri Nets organised by the CPN group at the Department of Computer Science, University of Aarhus, Denmark. The workshop papers are available in electronic form via the web pages: http://www.daimi.au.dk/pn2000/proceeding

    09091 Abstracts Collection -- Formal Methods in Molecular Biology

    Get PDF
    From 23. February to 27. February 2009, the Dagstuhl Seminar 09091 ``Formal Methods in Molecular Biology \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

    A critical review on modelling formalisms and simulation tools in computational biosystems

    Get PDF
    Integration of different kinds of biological processes is an ultimate goal for whole-cell modelling. We briefly review modelling formalisms that have been used in Systems Biology and identify the criteria that must be addressed by an integrating framework capable of modelling, analysing and simulating different biological networks. Aware that no formalism can fit all purposes we realize Petri nets as a suitable model for Metabolic Engineering and take a deeper perspective on the role of this formalism as an integrating framework for regulatory and metabolic networks.Research supported by PhD grant SFRH/BD/35215/2007 from the Fundacao para a Ciencia e a Tecnologia (FCT) and the MIT-Portugal program

    Efficient Simulation and Parametrization of Stochastic Petri Nets in SystemC: A Case study from Systems Biology

    Get PDF
    Stochastic Petri nets (SPN) are a form of Petri net where the transitions fire after a probabilistic and randomly determined delay. They are adopted in a wide range of appli- cations thanks to their capability of incorporating randomness in the models and taking into account possible fluctuations and environmental noise. In Systems Biology, they are becoming a reference formalism to model metabolic networks, in which the noise due to molecule interactions in the environment plays a crucial role. Some frameworks have been proposed to implement and dynamically simulate SPN. Nevertheless, they do not allow for automatic model parametrization, which is a crucial task to identify the network configurations that lead the model to satisfy temporal properties of the model. This paper presents a framework that synthesizes the SPN models into SystemC code. The framework allows the user to formally define the network properties to be observed and to automatically extrapolate, thorough Assertion-based Verification (ABV), the parameter configurations that lead the network to satisfy such properties. We applied the framework to implement and simulate a complex biological network, i.e., the purine metabolism, with the aim of reproducing the metabolomics data obtained in-vitro from naive lymphocytes and autoreactive T cells implicated in the induction of experimental autoimmune disorders

    On the Realisability of Chemical Pathways

    Full text link
    The exploration of pathways and alternative pathways that have a specific function is of interest in numerous chemical contexts. A framework for specifying and searching for pathways has previously been developed, but a focus on which of the many pathway solutions are realisable, or can be made realisable, is missing. Realisable here means that there actually exists some sequencing of the reactions of the pathway that will execute the pathway. We present a method for analysing the realisability of pathways based on the reachability question in Petri nets. For realisable pathways, our method also provides a certificate encoding an order of the reactions which realises the pathway. We present two extended notions of realisability of pathways, one of which is related to the concept of network catalysts. We exemplify our findings on the pentose phosphate pathway. Lastly, we discuss the relevance of our concepts for elucidating the choices often implicitly made when depicting pathways.Comment: Accepted in LNBI proceeding
    • 

    corecore