Numeric Databases

If users are inexperienced in searching for information, they should first consult search engines, meta-databases or portals (Table 5-6). Searchers who are familiar with databases may consult known databases (numeric databases, bibliographic databases, etc.) directly, being aware that they might miss new data sources (see Section 5.18). The reliability and quality of data are only given in peer-reviewed data sources. 

A database which contains numerical data, namely experimental values and/or calculated values. A statistical database, containing statistically processed data, is a type of numerical database. Numerical databases are normally stored in a field-oriented fashion in database tables. See Textual Database. 

In a new version of SECS, a transform library of 1291 basic reactions was extracted from a database of 14994 reactions. Indeed, in databases, numerous reactions are stored several times under different structural environments. For example, reduction of a ketone to an alcohol was present 78 times in the precedent one. The SPEK program uses transforms library from a database of 300(X) reactions. Blurock developed a system to extract, calculate, and organize chemical information from chemical databases. ... 

A strict separation of these three types of databases is difficult hence most databases contain a mixture of data types. Therefore the classification given here is based on the predominating data type. For example, the major emphasis of a patent database is on hterature, whereas it also comprises numeric and structural data. Another type is the integrated database, which provides a supplement of additional information, especially bibhographic data. Thus, different database types are merged, a textual database and one or more factual databases. 

Factual databases mainly contain alphanumeric data on chemical compounds. In contrast to bibliographic databases, factual databases directly describe the objects primary data on chemical compounds) and provide the required information on them. Factual databases can be divided into numeric databases, metadatabases, research project databases, and catalogs of chemical compounds. 

Numeric databases primarily contain numeric data on chemical compounds, such as physicochemical values and the results of series of measurements. Therefore, the files correspond to printed tables of numeric property data. Since the attributes of numeric data are different from those of text data, the search has to be managed... 

In addition to the numeric data (color, solubility, refraction index, spectra, etc.), these factual databases also include a bibliographic section with references or sources and a section with information for the identification of a compound (e.g., name, CAS Registry Number, molecular weight). 

Typical numeric databases are Beilstein, Speclnfo, DETHERM, and the Cambridge Structural Database. 

Research project databases include information on abstracts and reports categorized by research projects. Such factual databases allow one to search for projects in various fields of science and technology wdth numeric and textual queries. 

Another numeric database including bibliographic information is DETHERM. 

ICSD is a numeric database with 65 000 inorganic crystal structures (December,... 

GenBank [32] is a text-numeric database of genetic sequences with more than 28 billion bases in 22 million sequences (January, 2003) from genetic research. The collection of all publidy available sequences is annotated with information such as sequence description, source organism, sequence length, or references. The database, estabhshed in 1967, is updated daily and produced by the National Center for Biotechnology Information (USA). 

The protein sequence database is also a text-numeric database with bibliographic links. It is the largest public domain protein sequence database. The current PIR-PSD release 75.04 (March, 2003) contains more than 280 000 entries of partial or complete protein sequences with information on functionalities of the protein, taxonomy (description of the biological source of the protein), sequence properties, experimental analyses, and bibliographic references. Queries can be started as a text-based search or a sequence similarity search. PIR-PSD contains annotated protein sequences with a superfamily/family classification. 

The Web-based graphical user interface permits a choice from numerous criteria and the performance of rapid searches. This service, based on the chemistry information toolkit CACTVS, provides complex Boolean searches. Flexible substructure searches have also been implemented. Users can conduct 3D pharmacophore queries in up to 25 conformations pre-calculated for each compound. Numerous output formats as well as 2D and 3D visuaHzation options are supplied. It is possible to export search results in various forms and with choices for data contents in the exported files, for structure sets ranging in size from a single compound to the entire database. Additional information and down-loadable files (in various formats) can be obtained from this service. 

KnowItAll Bio-Rad s SadtlerT software database solutions for spectroscopy numeric IR, NMR, MS, NIR, and Raman data Bio-Rad Laboratories, Inc. commercial CD-ROM periodi- cally www.bio-rad.- com... 

The abbreviation QSAR stands for quantitative structure-activity relationships. QSPR means quantitative structure-property relationships. As the properties of an organic compound usually cannot be predicted directly from its molecular structure, an indirect approach Is used to overcome this problem. In the first step numerical descriptors encoding information about the molecular structure are calculated for a set of compounds. Secondly, statistical methods and artificial neural network models are used to predict the property or activity of interest, based on these descriptors or a suitable subset. A typical QSAR/QSPR study comprises the following steps structure entry or start from an existing structure database), descriptor calculation, descriptor selection, model building, model validation. 

Herbicides are also sometimes classified according to mode of action, selectivity, registered uses, and toxicity. The ever-increasing importance of herbicides and other pesticides and agrochemicals to a wide range of users, regulators, and researchers has led to the development of multiple and extensive computer databases. The primary database resources contain collected information relevant to herbicides, and numerous resource pubHcations are available to those needing information on the various aspects of herbicides (2). 

The foUowing tables outline the bibhographic, business, stmcture, numeric, spectra, and reaction databases currentiy available their producers and vendors and the subject matter they cover. 

Numeric. Researchers routinely use reported numeric measurements and data in thek work. Handbooks have been the primary source for locating this type of information, but numeric databases are now increasing in availabiUty. Advantages of searching numeric databases on-line include ease of use, dkect access to desked data, and abiUty to manipulate the information in the answer set. 

TDS UMERICA. This is another source for numeric databases (58). This company provides different on-line databases and software for chemistry, engineering, and environmental data. A summary of its databases is contained ia Table 7. 

OtherD t b ses. Available from different vendors (Table 8). For example, the researcher can obtain physical properties by usiag the Merck Index Online or the Dictionary of Organic Compounds available by Chapman and Hall Chemical Database. In DIALOG, numeric databases are collected under the name of CHEMPROP. 

CS4JSI/SND. The Canadian Scientific Numeric Database Service (CAN/ SND) is provided by the Canada Institute for Scientific and Technical Information (ClSTl), a division of the National Research Council of Canada. It contains 140,000 ir spectra of 96,000 compounds. Entries consist of peak locations and some intensities. This system is searchable on-line using the SPIR (Search Program for Infrared Spectra) (85). Table 9 summarizes the available databases in the area of spectra. 

Integrated Systems. Until recently, each of the numerous databases and sources of information available to chemists and technologists had to be searched iadividually, and selected results either ptinted for file storage or downloaded to an ia-house or private computer system for easy future access. 

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