04157oam 2200721I 450 991078403800332120230421043826.00-429-07777-71-4822-8342-51-280-07992-497866100799260-203-30429-210.1201/9781482283426 (CKB)1000000000334746(EBL)181531(OCoLC)475891948(SSID)ssj0000284005(PQKBManifestationID)11912567(PQKBTitleCode)TC0000284005(PQKBWorkID)10260961(PQKB)10064770(MiAaPQ)EBC181531(Au-PeEL)EBL181531(CaPaEBR)ebr10101069(CaONFJC)MIL7992(OCoLC)1000425491(EXLCZ)99100000000033474620180706d1998 uy 0engur|n|---|||||txtccrSecretory systems and toxins /edited by Michal Linial, Alfonso Grasso and Philip LazaroviciAmsterdam :Harwood Academic Publishers,1998.1 online resource (500 p.)Cellular and molecular mechanisms of toxin action,1026-4078 ;v. 2Description based upon print version of record.0-203-35387-0 90-5702-335-0 Includes bibliographical references and index.Book Cover; Title; Contents; Preface to the Series; Preface; Contributors; Synaptic Vesicle Proteins: A Molecular Study; Synaptic Vesicle Proteins: A Genetic Approach; Dissection of the Secretory Machinery; Vesicular Trafficking on the Late Secretory Pathway in the Budding Yeast, S. Cerevisiae: Yeast as a Genetic Tool in Which to Explore Protein Export; Regulatory Roles for Lipids in Vesicle Trafficking and Secretion; Fusion Proteins and the Fusion Events; Tetanus Toxin as a Valuable Pharmacological Tool for Studying Polysialogangliosides in Neuronal Signal TransductionMolecular Mechanisms of the Action of Clostridium Botulinum Type B Neurotoxin-Latrotoxin Receptors; Neurotoxins and Safety-Latches of the Secretory Process; Bacterial Neurotoxins in Invertebrates: Aplysia and the Deciphering of the Mode of Action of Clostridial Neurotoxins; Chromaffin Cells as a Secretory System: The Use of Neurotoxins; External Ions and -Latrotoxin Action; Botulinum Neurotoxins and their Substrates; Clostridial Neurotoxins as Enzymes: Structure and Function; Purification, Function and Selectivity in -LatrotoxinNeurotoxins, Cytoskeletons and Calcium Channels: Functional Studies at Mammalian Synapses Formed in CultureThe Synapsins and Neurotransmission; Morphological Studies of the Secretory Machinery Using Neurotoxin Probes; Membrane Fusion Protein Annexin VII: A Ca2+-Activated GTPase Target for Mastoparan in Secreting Chromaffin Cells; Glossary; IndexThis volume deals with the relationships between toxins and one of the most fundamental processes in any living cell - the secretory cycle. The reader will find up-to-date information on secretion, generated by experts in this fast evolving field. In the last decade extensive molecular and cellular studies have exposed the molecular similarity among most known secretory systems. In this book secretion is discussed from its basic mode found in yeast up to its most sophisticated version in neurotransmitter release in nerve terminals. A comprehensive view on the mode of action of toxins which bloCellular and molecular mechanisms of toxin action ;v. 2.SecretionToxinsNeurotoxic agentsSecretion.Toxins.Neurotoxic agents.571.79Grasso Alfonso100938Lazarovici Philip99566Linial Michal1519468MiAaPQMiAaPQMiAaPQBOOK9910784038003321Secretory systems and toxins3757603UNINA03824nam 22006495 450 991030075550332120200703133616.09781484233368148423336010.1007/978-1-4842-3336-8(CKB)4100000001382202(DE-He213)978-1-4842-3336-8(MiAaPQ)EBC5205531(CaSebORM)9781484233368(PPN)222231394(OCoLC)1020493769(OCoLC)on1020493769(EXLCZ)99410000000138220220171220d2018 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierAssessing and Improving Prediction and Classification Theory and Algorithms in C++ /by Timothy Masters1st ed. 2018.Berkeley, CA :Apress :Imprint: Apress,2018.1 online resource (XX, 517 p. 26 illus., 8 illus. in color.) 9781484233351 1484233352 Includes bibliographical references and index.1. Assessment of Numeric Predictions -- 2. Assessment of Class Predictions -- 3. Resampling for Assessing Parameter Estimates -- 4. Resampling for Assessing Prediction and Classification -- 5. Miscellaneous Resampling Techniques -- 6. Combining Numeric Predictions -- 7. Combining Classification Models -- 8. Gaiting Methods -- 9. Information and Entropy -- References.Carry out practical, real-life assessments of the performance of prediction and classification models written in C++. This book discusses techniques for improving the performance of such models by intelligent resampling of training/testing data, combining multiple models into sophisticated committees, and making use of exogenous information to dynamically choose modeling methodologies. Rigorous statistical techniques for computing confidence in predictions and decisions receive extensive treatment. Finally, the last part of the book is devoted to the use of information theory in evaluating and selecting useful predictors. Special attention is paid to Schreiber's Information Transfer, a recent generalization of Grainger Causality. Well commented C++ code is given for every algorithm and technique. You will: Discover the hidden pitfalls that lurk in the model development process Work with some of the most powerful model enhancement algorithms that have emerged recently Effectively use and incorporate the C++ code in your own data analysis projects Combine classification models to enhance your projects.Big dataArtificial intelligenceMathematical statisticsStatisticsBig Datahttps://scigraph.springernature.com/ontologies/product-market-codes/I29120Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Probability and Statistics in Computer Sciencehttps://scigraph.springernature.com/ontologies/product-market-codes/I17036Statistics, generalhttps://scigraph.springernature.com/ontologies/product-market-codes/S0000XBig data.Artificial intelligence.Mathematical statistics.Statistics.Big Data.Artificial Intelligence.Probability and Statistics in Computer Science.Statistics, general.005.133Masters Timothyauthttp://id.loc.gov/vocabulary/relators/aut105163UMIUMIBOOK9910300755503321Assessing and Improving Prediction and Classification2528352UNINA