The Role of Model Integration in Complex Systems Modelling

With no similar books on the market, this volume is a welcome addition. Many current methods use 'shallow integration' that employ output-input linking. This book goes further, setting out a systems biology and tumour modeling method called 'deep integration'.

Model integration the process by which different modelling efforts can be brought together to simulate the target system is a core technology in the field of Systems Biology. In the work presented here model integration was addressed directly taking cancer systems as an example. An in-depth literature review was carried out to survey the model forms and types currently being utilised. This was used to formalise the main challenges that model integration poses, namely that of paradigm (the formalism on which a model is based), focus (the real-world system the model represents) and scale.

A two-tier model integration strategy, including a knowledge-driven approach to address model semantics, was developed to tackle these challenges. In the first step a novel description of models at the level of behaviour, rather than the precise mathematical or computational basis of the model, is developed by distilling a set of abstract classes and properties. These can accurately describe model behaviour and hence describe focus in a way that can be integrated with behavioural descriptions of other models. In the second step this behaviour is decomposed into an agent-based system by translating the models into local interaction rules.

The book provides a detailed and highly integrated presentation of the method, encompassing both its novel theoretical and practical aspects, which will enable the reader to practically apply it to their model integration needs in academic research and professional settings. The text is self-supporting. It also includes an in-depth current bibliography to relevant research papers and literature. The review of the current state of the art in tumour modelling provides added value.

First book on Complex Systems Science And Systems Biology of Cancer with outstanding importance for systems biology and tumour modeling Contains advanced mathematical and computation principles applied to complex systems theory using tumours as an example Includes an in-depth critical study of the current state of the literature concerning modelling and simulation of tumour systems

Autorentext
Manish Patel ist SAP-Experte mit mehr als 15 Jahren Erfahrung in der IT-Branche. Nach seinem Abschluss an der Universität in Bombay war er in einem indischen Softwareunternehmen tätig und betreute mehrere Projekte im Finanzwesen im Raum Asien-Pazifik. Nachdem er so eine solide Grundlage in den verschiedenen Bereichen der Softwareentwicklung erworben hatte, begann er seine Karriere als SAP-Berater. Während der letzten zehn Jahre hat Manish Patel an den unterschiedlichsten SAP-Projekten in zahlreichen verschiedenen Branchen mitgearbeitet. Zudem hat er einige SAP-Schulungen für SAP America durchgeführt. In seinen SAP-Projekten war er sowohl für die Systemkonfiguration als auch für das Projektmanagement verantwortlich. Zurzeit arbeitet er als Senior SAP Solutions Consultant in Nordkalifornien.

Inhalt
Nature to Numbers: Complex Systems Modelling of Cancer.- Coping with Complexity: Modelling of Complex Systems.- Complexity and Model Integration: Formalisations.- Novel Strategies for Integrating Models into Systems-Level Simulations.- Experiments in Model Integration.- Discussion.