This, the 4th Transactions on Computational Systems Biology volume, contains carefully selected and enhanced contributions presented at the first Converging Science conference held at the University of Trento, Italy, in December 2004. Dedicated especially to models and metaphors from biology to bioinformatics tools, the 11 papers selected for the special issue cover a wide range of bioinformatics research, such as foundations of global computing, interdisciplinarity in innovation initiatives, biodiversity, and more.
The 5th Transactions on Computational Systems Biology volume, edited by Gordon Plotkin, features carefully selected and enhanced contributions initially presented at the 2005 IEEE International Conference on Granular Computing. The 9 papers selected for this special issue discuss various aspects of computational methods, algorithm and techniques in bioinformatics such as gene expression analysis, biomedical literature mining and natural language processing, protein structure prediction, biological database management and biomedical information retrieval.
This book covers Computational Models for Cell Processes, featuring enhanced contributions from the CompMod workshop (2009). Covers a wide range of topics in systems biology, addressing the dynamics and the computational principles of this emerging field.
The LNCS journal Transactions on Computational Systems Biology is devoted to inter- and multidisciplinary research in the fields of computer science and life sciences and supports a paradigmatic shift in the techniques from computer and information science to cope with the new challenges arising from the systems oriented point of view of biological phenomena. This issue contains four highly detailed papers. The first paper focuses on quantitative aspects of the bgl operon for E.coli. The second contribution deals with ecosystem transitions affecting phenotype expressions and selection mechanisms. The third paper presents the Stochastic Calculus of Looping Sequences (SCLS) suitable for the description of microbiological systems, such as cellular pathways, and their evolution. The final contribution describes the use of biological transactions to make atomic sequences of interactions in the BlenX language.
This issue on Computational Models for Cell Processes is based on a workshop that took place in Turku, Finland, May 2008. The papers span a mix of approaches to systems biology, ranging from quantitative techniques to computing paradigms inspired by biology.
This book presents a set of 14 papers accompanying the lectures of leading researchers given at the 8th edition of the International School on Formal Methods for the Design of Computer, Communication and Software Systems, SFM 2008, held in Bertinoro, Italy in June 2008. SFM 2008 was devoted to formal techniques for computational systems biology and covered several aspects of the field, including computational models, calculi and logics for biological systems, and verification and simulation methods. The first part of this volume comprises nine papers based on regular lectures, the second part of this volume comprises five papers based on talks given by people involved in the Italian BISCA research project on Bio-Inspired Systems and Calculi with Applications.
This book constitutes the refereed proceedings of the International Conference on Computational Methods in Systems Biology, CMSB 2007, held in Edinburgh, Scotland, September 2007. The 16 revised full papers presented present a variety of techniques from computer science, such as language design, concurrency theory, software engineering, and formal methods, for biologists, physicists, and mathematicians interested in the systems-level understanding of cellular processes.
Technology is taking us to a world where myriads of heavily networked devices interact with the physical world in multiple ways, and at many levels, from the globalInternetdowntomicroandnanodevices. Manyofthesedevicesarehighly mobile and autonomous and must adapt to the surrounding environment in a totally unsupervised way. A fundamental research challenge is the design of robust decentralized c- puting systemsthat arecapableofoperating in changing environmentsandwith noisy input, and yet exhibit the desired behavior and response time, under c- straints such as energy consumption, size, and processing power. These systems should be able to adapt and learn how to react to unforeseen scenarios as well as to display properties comparable to social entities. The observation of nature has brought us many great and unforeseen concepts. Biological systems are able to handle many of these challenges with an elegance and e?ciency far beyond currenthumanartifacts. Basedonthisobservation,bio-inspiredapproacheshave been proposed as a means of handling the complexity of such systems. The goal is to obtain methods to engineer technical systems, which are of a stability and e?ciency comparable to those found in biological entities. This Special Issue on Biological and Biologically-inspired Communication contains the best papers from the Second International Conference on Bio- Inspired Models of Network, Information, and Computing Systems (BIONET- ICS 2007). The BIONETICS conference aims to bring together researchers and scientistsfromseveraldisciplines incomputerscienceandengineeringwhereb- inspired methods are investigated, as well as from bioinformatics, to deepen the information exchange and collaboration among the di?erent communities.
Since the first edition of Stochastic Modelling for Systems Biology, there have been many interesting developments in the use of "likelihood-free" methods of Bayesian inference for complex stochastic models. Having been thoroughly updated to reflect this, this third edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. New methods and applications are included in the book, and the use of R for practical illustration of the algorithms has been greatly extended. There is a brand new chapter on spatially extended systems, and the statistical inference chapter has also been extended with new methods, including approximate Bayesian computation (ABC). Stochastic Modelling for Systems Biology, Third Edition is now supplemented by an additional software library, written in Scala, described in a new appendix to the book. New in the Third Edition New chapter on spatially extended systems, covering the spatial Gillespie algorithm for reaction diffusion master equation models in 1- and 2-d, along with fast approximations based on the spatial chemical Langevin equation Significantly expanded chapter on inference for stochastic kinetic models from data, covering ABC, including ABC-SMC Updated R package, including code relating to all of the new material New R package for parsing SBML models into simulatable stochastic Petri net models New open-source software library, written in Scala, replicating most of the functionality of the R packages in a fast, compiled, strongly typed, functional language Keeping with the spirit of earlier editions, all of the new theory is presented in a very informal and intuitive manner, keeping the text as accessible as possible to the widest possible readership. An effective introduction to the area of stochastic modelling in computational systems biology, this new edition adds additional detail and computational methods that will provide a stronger foundation for the development of more advanced courses in stochastic biological modelling.
