Complexity in biological information processing
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.
33 pages matching feedback in this book
Results 1-3 of 33
What people are saying - Write a review
We haven't found any reviews in the usual places.
Terence Sejnowski Introduction
Matthias G von Herrath Design of immunebased interventions in autoimmunity
diffuse feedback via a diffuse
11 other sections not shown
action potential firing action potentials aequorin Aertsen amplitude autoimmune behaviour Berridge Biol brain Brenner c-fos Ca2+ Ca2+ signalling Ca2+ spike Ca2+ transients calcium calmodulin CaMKII cascade cell types cellular coding fraction Complexity in biological components computation cortex CREB cytokines cytoplasm dendrite depends Diesmann direction selectivity Dolmetsch dynamics encoding EPSP ERK activation example excitatory neurons expression patterns feedback frequency function gene expression genome GPCR growth factor Hebbian learning hormone hybridization images immune system information processing inhibition inhibitory input InsP3 interactions interneurons intracellular Ca2+ Iyengar kinetics Laughlin learning MAP kinase MAPK mechanisms membrane mitochondria model neuron modulation molecular molecules mouse neural neurons Neurosci Novartis phosphorylation photoreceptors physiological postsynaptic predict presynaptic protein kinase pulse Rap1 receptor regulation response role RTKs Schofl second messenger Segel Sejnowski sequence signal transduction signalling pathways specific spike train stimulus synaptic plasticity synchronous temporal coding temporal pattern tissue transcription tyrosine kinase visual