Anwendung „künstlicher Intelligenz”︁ in der Chemie; Das Auffinden von Substrukturen mittels Rechner

Adler, Bernhard; Eitner, Bernd; Herrmann, Annemarie; Sorkau, E

doi:10.1002/zfch.19840240702

Cited by 4 publications

References 33 publications

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Multidimensional spectroscopy

Bremser

Fachinger

1985

Magnetic Reson in Chemistry

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Intelligent programs for structure elucidation should be able to predict structural features, or even complete structures, for an unknown compound. This can be accomplished by substructure analysis of the topological matrices corresponding to the most similar reference spectra detected by a library search. A comparison of the results from different spectroscopic techniques ('H NMR, uC NMR, IR, MS) reflects the content of the individual data bases, and also the sensitivity of the specific physical experiment to structural changes. The results can be combined to yield multidimensional information on the probability of any given substructure, even without crosslinked libraries from varying sources. In connection with the structure generator and the uC NMR spectrum estimation in ACCESS, a prediction of novel structures is routinely possible, as exemplified by the analysis of the spectra of 3'-methylacetophenone and genipin. The great advantages of this approach lie in its high flexibility in omitting or adding information and the absence of hand-encoded rules, because knowledge of the system simply stems from its experience, i.e. the structure-oriented spectral data bases.

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Multidimensional spectroscopy

Bremser

Fachinger

1985

Magnetic Reson in Chemistry

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Anwendung „künstlicher Intelligenz”︁ in der Chemie; CAD/CAM‐Technologie zur Simulation von Molekülspektren im Echtzeitbetrieb

Adler

Binshuba

Herrmann

et al. 1986

Zeitschrift fuer Chemie

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Anwendung “künstlicher Intelligenz”in der Chemie;Computersimulationen von Struktur‐Eigenschafts‐Beziehungen

Adler

Dobers

Eitner³

et al. 1988

Zeitschrift fuer Chemie

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The proceedings of chemical structure descriptors for structure‐activity studies is proposed. These descriptors are based on the set of properties distributed in a topological space (molecular graph). It dominates perceptions of empirical descriptors or of autocorrelation descriptors from physical properties of atoms, for instance, of electronegativities, polarisations or volumes of chemical groups. The choice between these different methods is determined by the type of interactions of chemical compound with the receptor. By means of pattern recognition techniques you can make a classification of molecules on the base of the activity features. As well we obtaine fuzzy results with 75–95% probabilities only

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Anwendung „künstlicher Intelligenz”︁ in der Chemie; Das Auffinden von Substrukturen mittels Rechner

Cited by 4 publications

References 33 publications

Multidimensional spectroscopy

Multidimensional spectroscopy

Anwendung „künstlicher Intelligenz”︁ in der Chemie; CAD/CAM‐Technologie zur Simulation von Molekülspektren im Echtzeitbetrieb

Anwendung “künstlicher Intelligenz”in der Chemie;Computersimulationen von Struktur‐Eigenschafts‐Beziehungen

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