Large and frequently occurring substructures in organic compounds obtained by library search of infrared spectra

Вармуза, Курт; Penchev, Plamen; Scsibrany, H.

doi:10.1016/s0924-2031(98)00069-1

Cited by 14 publications

(8 citation statements)

References 16 publications

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“…Another set of approaches (e.g. knowledge-based systems, pattern recognition methods) is based on comparison of spectra of the compound with a spectral library of known chemical structures (Varmuza et al 1998(Varmuza et al , 1999. Practical applications of these interpretation methods for complex organic compounds, however, are still needed and depend on development of both chemometric methods and spectral libraries.…”

Section: Spectroscopic Calibration and Prediction Of Litter Organic Mmentioning

confidence: 99%

Organic matter quality in ecological studies: theory meets experiment

Joffre¹,

Ågren²,

Gillon³

et al. 2001

Oikos

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Despite its importance for the understanding of element cycles in ecosystems, organic matter (OM) quality has remained an elusive property that is difficult to measure. In this study, two new approaches, both of which taking into account the complete biochemical composition of the organic material during the decomposition process, have been combined to solve this problem. First, following the continuous‐quality theory where quality is defined as a measure of substrate availability to the decomposers, initial litter OM qualities of a range of plant species from two experiments on litter decomposition were estimated and resulted in highly accurate fits of observed mass loss during decomposition. Applying the same theory, qualities of the litters at all stages of decomposition were then calculated. By comparison, the initial qualities of the same litters were estimated from conventional chemical fractions and resulted in much lower accurate fits. Second, near‐infrared reflectance spectroscopy (NIRS), a highly precise physical method of characterising biochemical composition of OM, was used to obtain a unique spectral signature of each sample. Calibrations were performed between spectral data and calculated qualities on the first half of the sample set and the calibration equations were applied to the second half of the sample set. Results show that theoretical litter OM quality can be calibrated and predicted precisely using NIRS. OM quality, defined according to a theoretical concept of substrate availability to decomposers, then contains and summarises all the relevant biochemical information. We demonstrate how the combination of NIRS and theory allows us to accurately measure OM quality. Measurement of OM quality provides an access to a fundamental property of organic matter and opens up new possibilities for studying element cycles in ecosystems.

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Section: Spectroscopic Calibration and Prediction Of Litter Organic Mmentioning

confidence: 99%

Organic matter quality in ecological studies: theory meets experiment

Joffre¹,

Ågren²,

Gillon³

et al. 2001

Oikos

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“…Such a set of characteristic substructures can be automatically obtained for instance by the determination of maximum common substructures among the molecular structures. 10,11 The software SubMat provides full flexibility for the application of userdefined substructures. PCA.…”

Section: Methodsmentioning

confidence: 99%

“…Another approach builds a set of substructures that are characteristic for the molecular structures under investigation. Such a set of characteristic substructures can be automatically obtained for instance by the determination of maximum common substructures among the molecular structures. , The software SubMat provides full flexibility for the application of user-defined substructures.…”

Section: Methodsmentioning

confidence: 99%

Substructure Isomorphism Matrix

Вармуза

Scsibrany

2000

J. Chem. Inf. Comput. Sci.

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A substructure isomorphism matrix n x p contains binary elements describing which of the given p query structures (substructures) are part of the given n target structures (molecular structures). Such a matrix can be used to investigate the diversity of the target structures and allows the characterization and comparison of structural libraries. A quadratic substructure isomorphism matrix n x n is obtained if the same structures are used as molecular structures and as substructures; this matrix contains full information about the topological hierarchy of the n structures. A hierarchical arrangement of chemical structures is useful for the evaluation of results obtained from searches in structure databases.

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“…Characteristic structural properties of a set with n structures can be described by a set of appropriate substructures; in the applied approach each of them is the MCS of a pair of the given molecular structures (Scsibrany and Varmuza 1992;Varmuza et al, 1998Varmuza et al, , 1999. The applied method to generate a set with characteristic substructures has been described previously (Varmuza et al, 1998) and is only briefly summarized here.…”

Section: Characteristic Substructuresmentioning

confidence: 99%

Characteristic substructures in sets of organic compounds with similar infrared spectra

Penchev

Вармуза

2001

Computers & Chemistry

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A method based on the determination of maximum common substructures is applied for the generation of substructures which are characteristic for a given set of molecular structures. The molecular structures are from hitlists obtained by spectral library searches; the hitlists contain those reference compounds, which have infrared spectra most similar to that from the query compound. The influences of various parameters of this method are investigated with the aim to improve the relevance of the obtained substructures for the structure of the query compound.

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Large and frequently occurring substructures in organic compounds obtained by library search of infrared spectra

Cited by 14 publications

References 16 publications

Organic matter quality in ecological studies: theory meets experiment

Organic matter quality in ecological studies: theory meets experiment

Substructure Isomorphism Matrix

Characteristic substructures in sets of organic compounds with similar infrared spectra

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