Other Related Databases

A fundamentally different approach is used by PROCAT, which does not describe motifs in linear sequence but rather structural motifs, i. e. combinations of residues that occur in a similar position in the 3D-structure of protein family members170, 711. 

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The x,y,z coordinates of all atoms in published, refined three-dimensional structures have been deposited in the Protein Data Bank (Table 3-4).568 571 Many other related databases are available,572 e.g., covering molecular modeling,573 gene sequences, proteome data,574 and much, much more. A good way to keep up to date is to read the "computer comer" in Trends in Biochemical Sciences (TIBS). Most databases can be reached on the World Wide Web.572 A selected list is... 

Vendors and software specialists strive to overcome the limitations of their products by integrating additional functionality in their closed systems. These systems tend to force a separation between the primary data they were designed to handle and other related databases. Such separations are often cumbersome and artificial. Realising that users require combinations of functionality, some vendors have provided external hooks which are often insufficient. Such closed systems have significant limitations with some of the following far-reaching consequences ... 

There are numerous, absolutely essential databases, originally developed for proteins and nucleic acids, but by now covering many omics topics as well as more mundane items, such as thermochanical and spectroscopic properties of thousands of organic and small inorganic compounds. The three listed below direct one to numerous other related databases ... 

Other related coding languages are derived from enhancements of SMILES (XSMILES, SMARTS, SMIRKS, STRAPS, CHUCKLES, CHORTLES, CHARTS [22]). Each of them was designed to represent special molecular structures or to allow particular applications (polymers, mixtures, reactions, or database-handling). 

The characteristic of a relational database model is the organization of data in different tables that have relationships with each other. A table is a two-dimensional consti uction of rows and columns. All the entries in one column have an equivalent meaning (c.g., name, molecular weight, etc. and represent a particular attribute of the objects (records) of the table (file) (Figure 5-9). The sequence of rows and columns in the tabic is irrelevant. Different tables (e.g., different objects with different attributes) in the same database can be related through at least one common attribute. Thus, it is possible to relate objects within tables indirectly by using a key. The range of values of an attribute is called the domain, which is defined by constraints. Schemas define and store the metadata of the database and the tables. 

The relational database model was developed by Codd at IBM in 1970 [9]. Oracle provided the first implementation in 1979. The hierarchical database IMS was replaced by DB2, which is also an RDBMS. There exist himdreds of other DBMSs, such as SQL/DS, XDB, My SQL, and Ingres. 

MACCS-II enables direct interface with other database management systems, such as the Relational Database Management System (RDBMS) and Oracle, so that databases which contain text and numeric data for which special interfaces are normally needed can be constmcted. Eor example, an Oracle MACCS-II linked system is currendy being used by the National Institute on Dmg Abuse (113) to develop a database that will allow scientists to determine the molecular stmctures of cocaine and other controlled substances as well as designer dmgs. 

Relational databases can store unlimited numbers of results for every sample and unlimited samples for every request. The advantage of a relational DBMS over a more traditional hierarchical system, in which data sets may contain other data sets, is that the design of the database only has to consider relationships between data elements, not the number of instances for any given variable. 

The second stage was a statistical analysis of the data available from the NGSDC database and several other smaller databases to extract the frequency-magnitude (f-M) relations for earthquakes originating in widely different regions of the earth. 

Patient databases with genetic profiles, e.g. for cardiovascular diseases, diabetes, cancer, etc. may play an important role in the future for individual health care, by integrating personal genetic profile into diagnosis, despite obvious ethical problems. The goal is to analyse a patient s individual genetic profile and compare it with a collection of reference profiles and other related information. This may improve individual diagnosis, prophylaxis, and therapy. 

The DR lines link SWISS-PROT to other biomolecular databases. SWISS-PROT is currently linked to 29 different databases. The preceding example shows links to 19 different entries in 6 different databases. The cross references allow users to navigate to linked databases to retrieve part or all of the related information. The format of a DR line, except for cross references to PROSITE (Hofmann et al., 1999), Pfam (Bateman et al., 1999), and the EMBL nucleotide sequence databases (Stoesser et al., 1999), is the following ... 

All of the databases have two common search features similar and related. Similar searches within the current database, whereas related searches other Cabinet databases. 

A fingerprint similarity search is available within Empath by selecting similar in the summary of objects that includes structures. The related button finds similar structures in other Cabinet databases. 

Studies should also evaluate the route of exposure, timing and duration of exposure, species specificity of effects and any pharmacokinetic or other considerations that might influence human exposure. Information should also be obtained as relevant from the health-related database. 

Several potential peroxy radical measurement techniques exist in the realm of atmospheric chemistry studies, although most have been used only in the laboratory. The techniques are summarized in Table I. Possibly, some laboratory methods could be applied to atmospheric measurements. The database for ambient peroxy radical concentrations in the troposphere and stratosphere is meager. Much of the available stratospheric data yield concentrations of H02 higher than those calculated with computer models. The reasons for this systematic difference are not known. In the troposphere, more measurements are called for in conjunction with other related species such as ozone, NO, NOjNo2 andjcv It wiH also t>e appropriate to develop multiple methods, and, when they have reached maturity, to perform intercomparison studies. 

MACCS-II enables direct interface with other database management systems, such as Ihe Relational Database Management System RDBMS) and Oracle, so that databases that contain text and numeric data, for which special interfaces arc normally needed, can be constructed. 

The core of the EntityDictionaryDao is in the retrieve...() methods. Here we assume the entity dictionaries are stored in a relational database. They can also be accessed from other types of data sources, such as web service, XML, and flat files. The point is to transform them into something that can be accessed easily and quickly by CRS. Take a closer look at the retrievePersonnel() method. Like most other retrieve...() methods, retrievePersonnel() returns a Map. What is in the Map depends on what kind of lookups the clients want to use to access the personnel dictionary. In the context of CRS, the personnel data can be accessed by its entirety, the research site where the person is located, person id, person s full name, or person s username. Therefore, the Map that retrievePersonnel() returns has four Collections—an entire personnel list, a site-people map, a person id-person map, a person s full name-person map, and a username-person map. 

There are several examples on the Internet of websites that are actively working toward providing free and unrestricted access to scientific data for the scientific community and general public. One of the biggest examples that is also closely related to chemistry is PubChem (http //pubchem.ncbi.nhn.nih.gov/), an online database of chemical compounds, their structures, and chemical and other related data. PubChem not only provides its data online on its webpages, but it also makes the chemical content easily accessible using automated tools (in this case, compressed SDfiles containing tens of thousands of structures each are used). 

CML is the best known of the XML notations for capture of structural data, but several other formats use XML-based syntax. The Protein Data Bank (PDB) (http // www.wwpdb.org/) is the single worldwide repository for macromolecular structure data. A representation of the Brookhaven PDB is available in an XML format called PDBML (Westbrook et al. 2005). PDBML provides a way to export structures and information about them from a relational database. Another database that offers... 

Traditionally data, properties, information etc has been stored in files on computer disks. More recently, it has become common practice on Macintosh computers, when using Microsoft software or some UNIX applications, to use either extensions to the file name or the first few bytes in the file (or another file) to indicate some aspects of the data, for example that it is suitable for Microsoft Excel. While this approach is practical to indicate something about files containing columns of data, it is not appropriate to store information about the values in cells in spreadsheet or how it relates to data in other columns. This requires a relational database such as ORACLE, and for performance reasons the values in the cells may only be accessed via the ORACLE API (Application Programming Interface) or SQL (Standard Query Language), in other words, it is suggested that relational databases such as ORACLE should be viewed as sophisticated file systems which allow the values to be organised, efficiently stored, rapidly retrieved etc. 

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