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Titlebook: Networks: From Biology to Theory; Jianfeng Feng,Jürgen Jost,Minping Qian Book 2007 Springer-Verlag London 2007 Mathematica.algorithms.bioi

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發(fā)表于 2025-3-21 16:37:02 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Networks: From Biology to Theory
編輯Jianfeng Feng,Jürgen Jost,Minping Qian
視頻videohttp://file.papertrans.cn/664/663018/663018.mp4
概述The first book in this rapidly evolving area, covering mathematical theory and applications of mathematical theory to biology.A true interdisciplinary book with contributors from biology, computer sci
圖書封面Titlebook: Networks: From Biology to Theory;  Jianfeng Feng,Jürgen Jost,Minping Qian Book 2007 Springer-Verlag London 2007 Mathematica.algorithms.bioi
描述.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..
出版日期Book 2007
關(guān)鍵詞Mathematica; algorithms; bioinformatics; biology; computer; computer science; genes; genome; mathematics; net
版次1
doihttps://doi.org/10.1007/978-1-84628-780-0
isbn_softcover978-1-84996-609-2
isbn_ebook978-1-84628-780-0
copyrightSpringer-Verlag London 2007
The information of publication is updating

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https://doi.org/10.1007/978-1-84628-780-0Mathematica; algorithms; bioinformatics; biology; computer; computer science; genes; genome; mathematics; net
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Neuronal Model of Decision MakingWe have built a neuronal model of decision making. Our model performs a decision based on an imperfect discrimination between highly mixed stimuli, and expresses it with a saccadic eye movement, like real living beings. We use populations of integrate-and-fire neurons.
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