Computer program for the retrieval and assignment of chemical environments and shifts to facilitate interpretation of carbon-13 nuclear magnetic resonance spectra

Jezl, Barbara A.; Dalrymple, David L.

doi:10.1021/ac60352a047

Cited by 38 publications

(15 citation statements)

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“…Although massively influential in the development of expert systems in general, DEN-DRAL was never as successful in practice as some of its proponents claimed [146]. However, the techniques that were developed for generating structures have proved to be of widespread applicability, and systems based on a range of types of spectral data (including not just mass spectra but also nuclear magnetic resonance and infra-red spectroscopy) are widely used [149], as are systems for searching databases of spectra [150][151][152].…”

Section: Knowledge-based Systemsmentioning

confidence: 99%

“…Although massively influential in the development of expert systems in general, DENDRAL was never as successful in practice as some of its proponents claimed [146]. However, the techniques that were developed for generating structures have proved to be of widespread applicability, and systems based on a range of types of spectral data (including not just mass spectra but also nuclear magnetic resonance and infra-red spectroscopy) are widely used [149], as are systems for searching databases of spectra [150][151][152].Another application of expert systems to structural chemistry is the area of computer-aided synthesis design (CASD), as reviewed recently by Ott [153]. CASD was first suggested as a possible area of research in Vleduts' 1963 paper on automatic reaction indexing that has been mentioned in Section 5 above [33].…”

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From chemical documentation to chemoinformatics: 50 years of chemical information science

Willett

2008

Journal of Information Science

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This paper summarises the historical development of the discipline that is now called 'chemoinformatics'. It shows how this has evolved, principally as a result of technological developments in chemistry and biology during the past decade, from long-established techniques for the modelling and searching of chemical molecules. A total of 30 papers, the earliest dating back to 1957, are briefly summarised to highlight some of the key publications and to show the development of the discipline.Keywords: Chemical documentation; Chemical structures; Chemoinformatics; Drug discovery; History; Informatics; Molecules; Pharmaceutical research IntroductionChemistry is, and has been for many years, one of the most information-rich academic disciplines. The very first journal devoted to chemistry was Chemisches Journal, which was published 1778-1784 and then, under the name of Chemische Annalen, till 1803 [1]. The growth in the chemical literature during the 19 th century led to a recognition of the need for comprehensive abstracting and indexing services for the chemical sciences. The principal such service is Chemical Abstracts Service (CAS), which was established in 1907 and which acts as the central repository for the world's published chemical (and, increasingly, life-sciences) information. The size of this repository is impressive: at the end of its first year of operations, the CAS database contained ca. 12K abstracts; by the end of 2006, this had grown to ca. 25M abstracts with ca. 1M being added each year. Most chemical publications will refer to one or more chemical substances. The structures of these substances form a vitally important part of the chemical literature, and one that distinguishes chemistry from many other disciplines. The CAS Registry System was started in 1965 to provide access to substance information, initially registering just small organic and inorganic molecules but now also registering biological sequences [2]. At the end of 1965 there 1 Correspondence to: Prof. Peter Willett, Department of Information Studies, University of Sheffield, 211 Portobello Street, Sheffield S1 4DP, UK; p.willett@sheffield.ac.uk. Journal of Information Science, XX (X) 2007, pp. 1-24 © CILIP, DOI: 10.1177/0165551506nnnnnn 1 Peter Willettwere ca. 222K substances in the System; by the end of 2006 this had grown to ca. 89M substances, of which ca. one-third were small molecules and the remainder biological sequences, with ca. 1.5M being added each year. There are also many additional molecular structures in public databases such as the Beilstein Database [3], and corporate files, in particular those of the major pharmaceutical, agrochemical and biotechnology companies.The presence of chemical structures requires very different computational techniques from those used for processing conventional textual information. These specialised techniques -now referred to by the name of chemoinformatics as discussed further below -have developed steadily over the fifty years that have passed since the founding of the I...

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Section: Knowledge-based Systemsmentioning

confidence: 99%

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confidence: 99%

From chemical documentation to chemoinformatics: 50 years of chemical information science

Willett

2008

Journal of Information Science

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“…Observed chemical shifts can be used (13) to search through the CNMR file to retrieve all the spectra that have the same shift or shifts. A typical search of this sort is shown in Fig.…”

Section: Carbon-13 Nuclear Magnetic Resonance Search System (Cnmr)mentioning

confidence: 99%

A Computer-Based Chemical Information System

Heller¹,

Milne²,

Feldman³

1977

Science

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A considerable improvement in the power of computers in the 1960's prompted work at the National Institutes of Health (NIH) and at the headquarters of the Environmental Protection Agency (EPA) to explore the feasibility of an online chemical information system (1). Several capabilities were identified as necessary in such a system, including storage capacity, search and retrieval from libraries of chemical data, comnputer-assisted analysis of chemical data, and retrieval of information from the chemical literature. The types of numerical data under consideration included mass spectra, carbon-13 nuclear magnetic resonance (NMR) spectra, and x-ray diffraction data. Bibliographic data dealing with mass spectrometry and x-ray crystallography have also been incorporated into the system.In view of the well-known difficulties implicit in the use of batch-oriented computers in information retrieval, it was considered essential that an on-line interactive computer be used for these tasks and so the NIH PDP1O was chosen as the computer to be used in these experiments. A chemist who searches through a data base often possesses a good deal of information, perhaps poorly defined, that is related to the problem at hand. A Dr. Heller is a computer specialist in the Management and Information

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“…As a result, a number of such techniques have been the subject of recent investigation by both ourselves and others. These methods fall into the three broad categories of: parametric methods (which, in general, have relied on the development of linear additivity parameters) (14-19); heuristic methods (1)(2)(3)(4)20); and the use of similarity measures (of which, we consider spectral search systems to be one example) (12,14,21). The present results bear on the relative efficacy of learning machine (heuristic) interpretation of spectra as opposed to use of empirical peak occurrence probabilities for structural characterization via either Bayes or maximum likelihood classifiers.…”

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Classification of binary carbon-13 nuclear magnetic resonance spectra

Wilkins¹,

Brunner²

1977

Anal. Chem.

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A combined retrieval system based on three different spectrometric data: infrared, mass, and 13C NMR, as well as the corresponding data file structures are described. The identification of the compounds depends entirely upon their spectra. The retrieval system may be used either for searching all three types of spectra, two, or one only. The resutts of 300 test searches are presented and the accuracy, precision, performance, and similarity coefficients for all three search types are evaluated. The performances of infrared, mass, and I3C NMR spectra searches are 0.77, 0.91, and 0.95, respectively. The similarity coefficients for compound pairs are calculated with an algorithm based on WLNs of both compounds.

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Computer program for the retrieval and assignment of chemical environments and shifts to facilitate interpretation of carbon-13 nuclear magnetic resonance spectra

Cited by 38 publications

References 19 publications

From chemical documentation to chemoinformatics: 50 years of chemical information science

From chemical documentation to chemoinformatics: 50 years of chemical information science

A Computer-Based Chemical Information System

Classification of binary carbon-13 nuclear magnetic resonance spectra

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