3- dimensional data type

Ohject-bastd model data representation in many differenl data types supports temporal and higher- dimensional data objecis can be reused difficull to design DHMS slow perfonnanee... 

Large data sets such as screening data or results obtained by combinatorial experiments are made up of a large number of data records. Hence a data record may represent a chemical reaction or substance, for example its corresponding variables will define the corresponding reaction conditions or biological activities. Depending on the dimensionality or data type of the information, one-, two-, multidimensional, or specific data types can be identified. 

A typical plot of x vs./(x) is considered to have one coordinate dimension, the X, and one data dimension,/(x). These data sets are plotted as line graphs, bar graphs, and so forth. These types of plots are readily made with most spreadsheet programs as well as dedicated graphing programs. Figure 13.1 shows two graphs that are considered to have a one-dimensional data space. 

The structure of a SOM is different from that of the feedforward network. Instead of the layered structure of the feedforward network, there is a single layer of nodes, which functions both as an input layer and an output layer. In a feedforward network, each node performs a processing task, accepting input, processing it, and generating an output signal. By contrast, in a SOM, every node stores a vector whose dimensionality and type matches that of the samples. Thus, if the samples consist of infrared spectra, each node on the SOM stores a pseudo-infrared spectrum (Figure 12). The spectra at the nodes are refined as the network learns about the data in the database and the vector at each node eventually becomes a blended composite of all spectra in the database. 

Discriminant analysis (DA) performs samples classification with an a priori hypothesis. This hypothesis is based on a previously determined TCA or other CA protocols. DA is also called "discriminant function analysis" and its natural extension is called MDA (multiple discriminant analysis), which sometimes is named "discriminant factor analysis" or CD A (canonical discriminant analysis). Among these type of analyses, linear discriminant analysis (LDA) has been largely used to enforce differences among samples classes. Another classification method is known as QDA (quadratic discriminant analysis) (Frank and Friedman, 1989) an extension of LDA and RDA (regularized discriminant analysis), which works better with various class distribution and in the case of high-dimensional data, being a compromise between LDA and QDA (Friedman, 1989). 

FIGURE 6.8 (a) Different types of outliers when a three-dimensional data set is projected on a robust two-dimensional PC A subspace, with (b) the corresponding outlier map [44],... 

As an extension of our research program concerned with the elucidation of the mechanism of three-dimensional network formation in the radical polymerization of multivinyl compounds, we attempted to control network formation with the intention of collecting the basic data for the molecular design of three-dimensional vinyl-type polymers with high performance and high limctionality. 

New SQL functions and data types can be used to extend a relational database. This is explained in Chapter 10 using PostgreSQL as an example. Ways in which three-dimensional molecular structures can be stored are examined in Chapter 11. This chapter also advocates using an RDBMS instead of molecular structure files and shows how this transition might be accomplished. 

Array Data Types for Two- and Three-Dimensional Coordinates... 

While atomic coordinates form the fundamental structure of a molecule, many methods prefer to represent a three-dimensional structure as a surface or a shape. Of course, these are ultimately computed from the atomic coordinates and perhaps atomic partial charges. It may be possible to represent these molecular surfaces or shapes as an array of three-dimensional coordinates. These could be stored as a column in the database analogous to the array of atomic coordinates. It might be necessary to create another data type, perhaps a composite data type, to store molecular surfaces or shapes. Once these representations are stored, they can be used in new SQL functions to assist in searching based on molecular surface or shape. 

With this definition, we can consider the structure representations of molecules in Section 7.2 as topological descriptors. At present, more than 5000 molecular descriptors can be computed [5]. They can be categorized by their data types (Table 7.11) or by their dimensionality (Table 7.12). 

Table 7.12 Molecular descriptors categorized by dimensionality of data. Data type Examples...

---