Numeric databases for chemical analysis

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Numeric Databases for Chemical Analysis

Databases for use with analytical chemistry instrumental techniques are surveyed, with attention to existing databases and collection efforts now underway, as well as needs for new data-bases. Collections of spectra for use in NMR, infrared spectroscopy, and mass spectroscopy are described. Using mass spectral databases as an example, a critique is presented of automated quality control procedu...

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CORE: Nonparametric Clustering of Large Numeric Databases

Current clustering techniques are able to identify arbitrarily shaped clusters in the presence of noise, but depend on carefully chosen model parameters. The choice of model parameters is difficult: it depends on the data and the clustering technique at hand, and finding good model parameters often requires time consuming human interaction. In this paper we propose CORE, a new nonparametric clu...

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Numeric Databases in Chemical Thermodynamics at the National Institute of Standards and Technology

During the past year the activities of the Chemical Thermodynamics Data Center and the JANAF Thermochemical Tables project have been combined to obtain an extensive collection of thermodynamic information for many chemical species, including the elements. Currently available are extensive bibliographic collections and data files of heat capacity, enthalpy, vapor pressure, phase transitions, etc...

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Scaffold Topologies. 2. Analysis of Chemical Databases

We have systematically enumerated graph representations of scaffold topologies for up to eight-ring molecules and four-valence atoms, thus providing coverage of the lower portion of the chemical space of small molecules (Pollock et al. J. Chem. Inf. Model., this issue). Here, we examine scaffold topology distributions for several databases: ChemNavigator and PubChem for commercially available c...

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Fingerprinting Numeric Databases with Information Preservation and Collusion Avoidance

Information age demands omnipresence of data. Large data sets are created, maintained and outsourced to the third party experts for data mining. Knowledge and patterns are extracted by using advanced data mining algorithms that assist the decision makers to ensure quick, correct and effective decisions to be made in this world of competition. The outsourcing of these large data sets faces the p...

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ژورنال

عنوان ژورنال: Journal of Research of the National Bureau of Standards

سال: 1989

ISSN: 0160-1741

DOI: 10.6028/jres.094.005