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Mathematical Chemistry and Chemoinformatics: Structure Generation, Elucidation and Quantitative Structure-Property Relationships de Adalbert Kerber

Mathematical Chemistry and Chemoinformatics: Structure Generation, Elucidation and Quantitative Structure-Property Relationships

Autor Adalbert Kerber, Reinhard Laue, Markus Meringer, Christoph Rücker, Emma Schymanski
en Mixed media product – 12 ian 2014
This work provides an introduction to mathematical modeling of molecules and its applications (structure generation, elucidation, evaluation; QSAR/QSPR etc.).It contains exercises and explanations of software packages in chemoinformatics that can be used directly via an online login code. It is aimed at users of structure generation and corresponding methods, but also for teaching and learning chemoinformatics and for software designers.
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Specificații

ISBN-13: 9783110300109
ISBN-10: 3110300109
Pagini: 520
Ilustrații: Includes a print version and an ebook
Dimensiuni: 170 x 240 mm
Ediția:Includes a print version and an ebook.
Editura: De Gruyter
Locul publicării:Berlin/Boston

Notă biografică

A.Kerber, R.Laue, U. Bayreuth; M.Meringer, DLR Oberpfaffenhofen; C.Rücker, Leuphana U. Lüneburg; E.Schymanski, EAWAG Dübendorf

Cuprins

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Chapter 1: Molecules in silico 1.1 Graphs, labeled and unlabeled 1.2 Molecular graphs, constitutional isomers 1.3 Summary Chapter 2: Substructures, reactions, descriptors 2.1 Substructures 2.2 Molecular substructures 2.3 Chemical reactions 2.4 Mesomerism 2.5 Existing chemical compounds 2.6 Molecular descriptors 2.7 Summary Chapter 3: Chirality 3.1 Orientation and chirality 3.2 Permutational isomers 3.3 Permutational isomers by content, in particular by racemic content 3.4 Enumeration by symmetry 3.5 Constructive aspects 3.6 Summary Chapter 4: Stereoisomers 4.1 Stereoisomers 4.2 Radon partitions 4.3 Binary Grassmann-Plücker relations 4.4 An example, cyclohexane 4.5 Summary Chapter 5: Molecular structure generation 5.1 Formula based molecular generation 5.2 Reaction based structure generation 5.3 Examples: Combinatorial libraries 5.4 Generic structural formulas 5.5 Example: Patents in chemistry 5.6 Canonizing molecules and graphs 5.7 Data structure for molecular graphs 5.8 Summary Chapter 6: Supervised statistical learning 6.1 Variables and predicting functions 6.2 Models for predicting functions 6.3 Summary Chapter 7: Structure-property relationships 7.1 Optimization of experiments in combinatorial chemistry 7.2 The use of molecular descriptors 7.3 Quantitative structure--property relationships 7.4 Example: Boiling points of alkanes 7.5 Example: Physical density of propyl acrylates 7.6 Example: Antibacterial activity of quinolones 7.7 Remarks on the real library 7.8 Summary Chapter 8: Molecular structure elucidation 8.1 Spectroscopic methods 8.2 The principle of automated molecular structure elucidation 8.3 Basics of mass spectrometry 8.4 Ranking functions for mass spectra 8.5 Classification of mass spectra 8.6 Automated structure elucidation via MS 8.7 High resolution MS 8.8 Molecular formulas from high-resolution MS and MS/MS 8.9 Summary Chapter 9: Case studies of CASE 9.1 Automated structure elucidation with MOLGEN-MS 9.2 Calculated properties to improve CASE 9.3 Examples of CASE at work Chapter 10: Appendix 10.1 Lists of molecular descriptors 10.2 Substructures for MS classifiers 10.3 Molecular formulas, according to mass and ion type 10.4 Isomers, by formula and mass 10.5 Summary