Networks: From Biology to Theory

Häftad, Engelska, 2010

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2010-10-13
Mått:155 x 235 x 19 mm
Vikt:517 g
Format:Häftad
Språk:Engelska
Antal sidor:318
Förlag:Springer London Ltd
ISBN:9781849966092

Utforska kategorier

Biovetenskap inom Naturvetenskap och teknik
Hårdvara inom Data och IT

Mer om författaren

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.

Innehållsförteckning

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.