Structured alphanumeric data

Structured alphanumeric data. These data types consist of mixed letters and numbers in a highly structured format of records and fields. Database programs accept these data types, including the specialised database programs used for specific purposes such as accident and incident recording. 

Questions and answers. This is a subcategory of the structured alphanumeric data but because it has special relevance to health and safety it is dealt with separately. Packages for active monitoring, audit, attitude surveys and measuring safety culture accept these types of data. 

Numerical data are in question, if spectral, chromatographic, or electroanalytical data have been measured and, if concentrations, errors, or analysis costs are to be stored. Typical alphanumeric data concern descriptions of sample identity or analytical procedures. Chemical structures are represented topologically from electron microprobe analysis. 

This displays a single chemical structure on an ORACLE screen with alphanumerical data (see Figure 5). 

Based on ORACLE and DARC a number of research information systems are being built in our company. Both programs have already been proven to be stable for many years. ORACLE will be used for all alphanumerical data of compounds and DARC for the related structures. T 16syst%mes has developed, in co-operation with Organon,... 

To summarize this item, a (sub)structure-graphical aspect is an essential background to any database dealing with chemical substances. A structure query is returned to the user as a unique descriptor which may then be linked to further alphanumeric data of any particular form. The remainder of this article... 

The user is often more interested in the contents than in the technical organization of databases. The wide variety of data allows the classification of databases in chemistry into literature, factual (alphanumeric), and structural types (Figure 5-10) [12, 13). 

A second, more sophisticated clustering technique for alphanumeric information proceeds as follows The data base can be imagined as a collection ot items which are described by a set ot properties. Again, our properties in the Merck Index data base are chemical structures as names, and medical use. Each item in the data base is assigned a vector whose column elements indicate whether the item has a given set ot properties or whether it does not. For example, a 1 indicates the presence ot the property and a zero indicates the absence ot the property (Table III). 

The conversion of chemical names and identihers into appropriate chemical structure representations offers the ideal path for chemists and organizations to mine chemical information. Because chemical names are not unique and a multitude of labels can map to a single chemical entity, the facile conversion of alphanumeric text identihers to a connection table representation enables superior data capture, representation, indexing, and mining. The industry s need to mine more information from both the historical corpus as well as new sources is obvious, and a number of researchers have initiated research into the domain of chemical identiher text mining and conversion. Multiple efforts have been made in the held of bioinformatics research,8 and, while interesting as a parallel, in this chapter we will focus the efforts to extract and convert identihers related to chemical entities rather than, for example, genes, enzymes, or proteins. 

In addition to the published literature, a chemical shift database is being developed by Advanced Chemistry Development (AC D/Labs) that can be used interactively by an investigator both to predict chemical shifts for a molecule being investigated and to search the database by a multitude of parameters, including structure, substructure, and alphanumeric text values. This database is accessible in the NNMR software package offered by ACD/Labs and presently contains data on more than 8800 compounds with over 20 700 chemical shifts. Examples of the use of the NNMR database will be presented later in this chapter. 

PDB-ID Codes. The structure record accessioning scheme of the Protein Data Bank is a unique four-character alphanumeric code, called a PDB-ID or PDB code. This scheme uses the digits 0 to 9 and the uppercase letters A to Z. This allows for over 1.3 million possible combinations and entries. Many older records have mnemonic names that make the structures easier to remember, such as 3INS, the record for insulin shown earlier. A different method is now being used to assign PDB-IDs, with the use of mnemonics apparently being abandoned. 

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