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Titlebook: Neurotransmitter Enzymes; Alan A. Boulton,Glen B. Baker,Peter H. Yu Book 1986 Springer Science+Business Media New York 1986

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書目名稱Neurotransmitter Enzymes
編輯Alan A. Boulton,Glen B. Baker,Peter H. Yu
視頻videohttp://file.papertrans.cn/665/664568/664568.mp4
叢書名稱Neuromethods
圖書封面Titlebook: Neurotransmitter Enzymes;  Alan A. Boulton,Glen B. Baker,Peter H. Yu Book 1986 Springer Science+Business Media New York 1986
描述Techniques in the neurosciences are evolving rapidly. There are currently very few volumes dedicated to the methodology - ployed by neuroscrentists, and those that are available often seem either out of date or limited in scope. This series is about the methods most widely used by modern-day neuroscientrsts and is written by their colleagues who are practicing experts. Volume 1 will be useful to all neuroscientists since it concerns those procedures used routinely across the wrdest range of s- disciplines. Collecting these general techniques together in a single volume strikes us not only as a service, but will no doubt prove of exceptional utilitarian value as well. Volumes 2 and 3 describe all current procedures for the analyses of amines and their metabolites and of amino acids, respectively. These collections will clearly be of value to all neuroscientists working in or contemplating research in these fields. Similar reasons exist for Volume 4 on receptor binding techniques since experimental details are provided for all types of ligand-receptor binding, including chapters on general principles, drug discovery and development, and a most useful-appendix on computer programs for
出版日期Book 1986
版次1
doihttps://doi.org/10.1385/0896030792
isbn_softcover978-1-4899-4130-5
isbn_ebook978-1-59259-610-2Series ISSN 0893-2336 Series E-ISSN 1940-6045
issn_series 0893-2336
copyrightSpringer Science+Business Media New York 1986
The information of publication is updating

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Prakash V. Sulakhe,Ramesh C. Gupta,Gowraganahalli Jagadeeshful tool in nonlinear dynamic system identification. Their system architecture is more suitable for controller design compared to alternative approximation methods. The main advantage is that linear controller design methods can be, at least locally, applied and combined with nonlinear optimization
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