Transactions on Computational Systems Biology XI: Computational Models for Cell Processes (Lecture Notes in Computer Science / Transactions on Computational Systems Biology)

by Corrado Priami (Editor), Ralph-JohanBack (Editor), IonPetre (Editor)

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  Paperback
  2009

  $89.55

  Biology is witnessing a transformation towards a more quantitative science, based on the major technological breakthroughs of the past decade. In this transformation, biology is incorporating mathematical modeling techniques and computational approaches towards numerical simulations, model analysis, and quantitativepredictions.An importantgoalis to formalizeandanalyzethe ev- changing inter-connections between components (often on di?erent time and space scales), their in?uence on one another, regulatory patterns, alternative pathways, etc. Formal reasoning rather than empirical observations is the main driving force in this new type of biological research.At the same time, computer science and applied mathematics are faced with considerable methodological challenges in handling an unprecedented level of concurrency, stochastic e?ects, amixoflargeandsmallpopulations,combinatorialexplosionsinthe statespace, model re?nement, and model (de)composition, etc. ThisspecialissueofTransactionsonComputationalSystemsBiologyonC- putationalModels forCellProcessesisbasedonaworkshopwith thesamename that took place in Turku, Finland, on May 27, 2008. The workshop was or- nized as a satellite event of the 15th International Symposium on Formal Me- ods that took place in Turku in the period May 28-31, 2008. This special issue however had an open call for paper submissions, with a separate peer-review process. The accepted papers span an interesting mix of approaches to systems biology, ranging from quantitative to qualitative techniques, from continuous to discrete mathematics, from deterministic to stochastic methods, from compu- tional models for biology to computing paradigms inspired by biology. Overall, they give a good glimpse into some of the exciting current research avenues in computational systems biology.