Mathematical Chemistry and Chemoinformatics - neues Buch

EAN (ISBN-13): 9783110300109
Erscheinungsjahr: 2014

Buch in der Datenbank seit 2014-03-27T15:22:16+01:00 (Berlin)
Detailseite zuletzt geändert am 2018-02-12T13:51:30+01:00 (Berlin)
ISBN/EAN: 9783110300109

ISBN - alternative Schreibweisen:
978-3-11-030010-9
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: rucker, rück, meri, schymanski christoph adalbert meringer reinhard kerber markus rücker emma laue, mering, kerb
Titel des Buches: chemoinformatics mathematical chemistry

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Daten vom Verlag:

Autor/in: Adalbert Kerber; Reinhard Laue; Markus Meringer; Christoph Rücker; Emma Schymanski
Titel: Mathematical Chemistry and Chemoinformatics - Structure Generation, Elucidation and Quantitative Structure-Property Relationships
Verlag: De Gruyter; De Gruyter
491 Seiten
Erscheinungsjahr: 2014-01-13
Berlin/Boston
Sprache: Englisch
209,00 € (DE)
209,00 € (AT)
Not available (reason unspecified)
Includes a print version and an ebook

SA; BB; EA; Hardcover, Softcover / Chemie/Theoretische Chemie; Chemie; MAT003000 MATHEMATICS / Applied; MAT008000 MATHEMATICS / Discrete Mathematics; MAT036000 MATHEMATICS / Combinatorics; SCI013010 SCIENCE / Chemistry / Analytic; Discrete mathematics; Combinatorics & graph theory; Applied mathematics; Analytical chemistry; Quantum & theoretical chemistry; Mathematical Chemistry; Chemoinformatics; Molecular Structure Generation; Mass Spectrometry; BB; EA

Chapter 1: Molecules in silico1.1 Graphs, labeled and unlabeled 1.2 Molecular graphs, constitutional isomers 1.3 SummaryChapter 2: Substructures, reactions, descriptors2.1 Substructures 2.2 Molecular substructures 2.3 Chemical reactions 2.4 Mesomerism 2.5 Existing chemical compounds 2.6 Molecular descriptors 2.7 SummaryChapter 3: Chirality3.1 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 SummaryChapter 4: Stereoisomers4.1 Stereoisomers 4.2 Radon partitions 4.3 Binary Grassmann-Plücker relations 4.4 An example, cyclohexane 4.5 SummaryChapter 5: Molecular structure generation5.1 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 SummaryChapter 6: Supervised statistical learning6.1 Variables and predicting functions 6.2 Models for predicting functions 6.3 SummaryChapter 7: Structure-property relationships7.1 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 SummaryChapter 8: Molecular structure elucidation8.1 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 SummaryChapter 9: Case studies of CASE9.1 Automated structure elucidation with MOLGEN-MS 9.2 Calculated properties to improve CASE 9.3 Examples of CASE at workChapter 10: Appendix10.1 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