Complexity in Biological Information Processing -No. 239 (Novartis Foundation Symposia) by Novartis Foundation

Product Description

Many human diseases arise from the malfunction of signalling components, in particular alterations of multiple components of an integrated signalling network. Experimental and computational tools to describe and quantify these changes are increasingly available, providing a wealth of data that can stimulate systematic analysis of the entire signalling network and enable prediction of disease states not easily recognizable from complex data sets.

This groundbreaking book explores the structural and temporal complexity in biological signalling exemplified in neuronal, immunological, humoral and genetic signal transduction networks. With discussions between experimentalists and theoretically oriented scientists, this book takes an interdisciplinary approach that may help switch the analysis of biological signalling from descriptive to predictive science and capture the behaviour of entire systems.

* Explores the structural and temporal complexity in biological signalling.
* Represents an unusual collocation of three different areas: immunology, cell signalling and neural networks.
* Contains interdisciplinary discussions between experimentalists and theoretically oriented scientists, in particular those working on computer simulations.

Product Details

* Amazon Sales Rank: #3272366 in Books
* Published on: 2001-10-15
* Number of items: 1
* Binding: Hardcover
* 258 pages

Editorial Reviews

Book Info
(Novartis Foundation) Presents the proceedings on the Symposium on Complexity in Biological Information Processing, held at the Kaiserin-Freidrich-Haus, Berlin, Germany, on July 4-6, 2000.

From the Back Cover
Many human diseases such as cancer, diabetes and neural disorders arise from the malfunction of signalling components. This is frequently not caused by a single defect but is due to alterations to multiple components of an integrated signalling network. Experimental tools to quantify such changes precisely and describe the interconnected multichain signalling pathways in health and disease in a time-resolved manner are becoming increasingly available, resulting in a exponential increase in detailed information. For the unaided human mind, classification of this wealth of data and understanding the implications for pathophysiology is getting more and more difficult. Computational tools are a prerequsiite for understanding of the complex interactions in biological information processing from the vast array of experimental data. These tools are starting to take shape. They have the potential to integrate many details into a systematic analysis of the entire signalling network and enable prediction of diease states not easily recognizable from complex data sets. This approach may thus help to switch the analysis of biological signalling from descrptive to predictive science and capture in a more general way the behaviour of entire systems. This groundbreaking book explores the structural and temporal complexity in biological signalling exemplified in neuronal, immunological, humoral and genetic signal transduction networks. It contains interdisciplinary discussions between experimentalists and theoretically oriented scientists, in particular those working on computer simulations. Synthesis of experiment, theory and simulation should help to explain disorders of the regulation of complex biological networks and may lead to a new understanding of many human diseases.