Process Calculi Abstractions for Biology

Several approaches have been proposed to model biological systems by means of the formal techniques and tools available in computer science. To mention just a few of them, some representations are inspired by Petri Nets theory, and some other by stochastic processes. A most recent approach consists in interpreting the living entities as terms of process calculi where the behavior of the represented systems can be inferred by applying syntax-driven rules. A comprehensive picture of the state of the art of the process calculi approach to biological modeling is still missing. This paper goes in the direction of providing such a picture by presenting a comparative survey of the process calculi that have been used and proposed to describe the behavior of living entities. This is the preliminary version of a paper that was published in Algorithmic Bioprocesses. The original publication is available at http://www.springer.com/computer/foundations/book/978-3-540-88868-

09091 Abstracts Collection -- Formal Methods in Molecular Biology

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

Modelling Biological Systems From Molecular Interactions to Population Dynamics

Biological systems are examples of complex systems, which consist of several interacting components. Understanding the behaviour of such systems requires a multidisciplinary approach that encompasses biology, mathematics, computer science, physiscs and chemistry. New research areas are emerging as the result of this multidisciplinarity, such as bioinformatics, systems biology and computational biology. Computer science plays an important role in the newly emerging research areas by offerring techniques, algorithms, languages and software to solve research problems efficiently. On the other hand, the efforts to solve these research problems stimulate the development of new and better computer science techniques, algorithms, languages and software. This thesis describes our approach in modelling biological systems as a way to better understand their complex behaviours. Our approach is based on the Calculi of Looping Sequences, a class of formalisms originally developed to model biological systems involving cells and their membrane-based structures. We choose Stochastic CLS and Spatial CLS, two variants of the calculi that support quantitative analysis of the model, and define an approach that support simulation, statistical model-checking and visualisation as analysis techniques. Moreover, we found out that this class of formalisms can be easily extended to model population dynamics of animals, a kind of biological systems that does not involve membrane-based structures

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Graduate Catalogue 2004-2005

https://scholarship.shu.edu/graduate_catalogues/1045/thumbnail.jp