Bioinformatics is the hottest topic in computer science. Each leading computer science department in UK has a group specialising in Bioinformatics or Computational Biology (system biology). The most important journal (according to impact factor) in computer science is "Bioinformatics" (~6). In Warwick, the University contributed £2.5 million to set up a System Biology Centre and is applying to BBSRC for £8.5 million in funding.

At the moment, we have accumulated a huge body of data about single variables (genes, proteins, neurons etc), but we are still far away from being clear about holistic issues arising from metabolic networks, gene networks, protein networks and neuronal networks. Progress is made by collecting, visualizing, and analyzing data using disparate fields such as image processing, database design and machine learning, and then modelling networks and predicting network outcomes based upon this data.

This book brings together leading scientists (computer scientists, applied mathematicians, and biologists) from Germany, China, USA and UK to discuss and present the most up-to-date results in the area.

Autorentext

Many invited speakers are quite senior people in the area. For example, Prof. Ritter and Prof. Jost won the Lebnitz Prize in Germany, which is the highest prize in Germany. There are many senior people from China as well and the invited speakers are from Qinhua, Peking, Fudan etc. University, covering almost all leading universities in China. Prof. Zhang, from Cold Spring USA (arguably the best institute in biology in the world), is the leading biologist working in the area.

Klappentext

During the past decades, we have witnessed the thriving development of new mathematical, computational and theoretical approaches such as bioinformatics and neuroinformatics to tackle some fundamental issues in biology. These scientific approaches focus no longer on individual units, such as nerve cells or genes, but rather on the emerging dynamic patterns of interactions between them. These concentrate on the interplay between the local dynamics and activity transmissions on one side and the global structure of the underlying connection scheme on the other hand.

In this light, the concept of a network emerges as a powerful and stimulating research paradigm in mathematics, physics and computer science, and demonstrates a very lively interaction between experimental findings, simulation studies, and theoretical investigations that then in turn lead to new experimental questions.

This volume explores this concept in full and features contributions from a truly global set of contributors, many of whom are pre-eminent in their respective fields.

Zusammenfassung

After over a century of research, we still do not understand the principle by which a stimulus, such as an odour or a sound, is represented by distributed neural ensembles within the brain; by which an individual is developed by the control of gene networks. While past studies have made detailed analysis of response profiles of single cells and the properties of a single gene in isolation, such techniques and approaches cannot easily address holistic issues of how large ensembles of neurons and genes can integrate information both spatially and temporally. There is little doubt that much of the info processing power of the brain or a gene network resides in the activities of co-operating and competing networks of neurons and genes and that if we unlock the principles whereby info is encoded and processed within these networks as a whole, rather than within single neurones or genes in isolation, we may be able to understand how the brain or gene network works. Our book will contribute to the development of such a study.

Inhalt
Theory.- The Category of X-Nets.- Networks with Delays.- Dynamical Networks.- Applications in Neuroscience.- Neuronal Computation Using High-Order Statistics.- Neuronal Model of Decision Making.- Estimation of Spike Train Statistics in Spontaneously Active Biological Neural Networks.- Physiology and Related Models of Associative Visual Processing.- Gestalt Formation in a Competitive Layered Neural Architecture.- Applications in Bioinformatics.- Regulatory Signals in Genomic Sequences.- Dynamic Properties of Cell-Cycle and Life-Cycle Networks in Budding Yeast.- Understanding Protein-Protein Interactions: From Domain Level to Motif Level.- An Efficient Algorithm for Deciphering Regulatory Motifs.- The Stochastic Model and Metastability of the Gene Network.- Messenger RNA Information: Its Implication in Protein Structure Determination and Others.