Organism-specific databases

In some databases, material-specific data are present for various waste treatment options. Plastics generally are among the materials included. However, no specific data on additives are found. In case of incineration, organic additives break down and therefore are not expected. In case of landfill, some leaching of evaporation would be probable, but cannot be found in the data. 

Huijbregts M, Margni M, van de Meent D, Jolliet O, Rosenbaum RK, McKone T, Hauschild M (2010) USEtox Chemical-specific database organics. http //www.usetox.org/(2010-04-07)... 

NCBI provides several genomic biologytods and resources, including organism-specific pages that include links to many web sites and databases relevant to that species. We invite you to explore the links provided on this page. 

TmPrime includes a codon optimizing feature. It implements global codon optimization that replaces each codon based on the organism-specific codon frequencies using the organism-specific codon data in the Codon Usage Database (http//www.kazusa. 

Content-related fields are information type , use of chemicals , number of chemicals , and descriptor . A few data-sources specialize in types of information, e.g., ecotoxicity or identification parameters. On the other hand, there exist special databases for specific uses of chemical substances, e.g., pesticide databases. As there are databases which contain thousands of chemicals and others which only describe hundreds, the field number of chemicals is given. For a comprehensive description of the content of a source, a thesaurus containing key words which are of interest to the problem of environmental chemicals, has been developed. These key words can be found in the descriptor field. The thesaurus, which takes into account most of the parameters required by the German Chemicals Act for registering chemical substances, treats not only environmental but also health and worlqrlace exposure aspects. The thesaurus encompasses, for example, the identification of chemicals, data on detection of chemicals in the environment, use of chemicals, economic data, physical-chemical properties, degradation and accumulation data, ecotoxicity, eff ects on wildlife, toxicity effects on mammals, effects on human organisms, information in relation to the workplace, etc. 

One of the oldest types of database and still the most widespread. A relational database organizes the stored data items into tables in which the columns are fields of a specific type and the rows are data entries. The typical query language for relational databases is SQL (systems query language), which is powerful, well defined and, within the domain of the SQL standard, independent of the database vendor. See. Full-text Database Object-oriented Databa.se and Object-Relational Database. 

Usually an Internet user learns after a while where to go for specific information The Browser provides a bookmark tlmction where all these addresses can be organized by different subjects Typical bookmark folders are Societies, Companies, Journals, Institutes, Databases, Search engines The NDTnet Journal provides a virtual library that makes it easy for newcomers to find NDT sites. Unfortunately, some sites provide a lot of information but do not offer a search function. 

Most database users do not know how the data are organized in a database system (DBS) they depend solely on the application programs. This is sufficient for most database searches where users can receive large amounts of results quickly and easily, e.g., on literature or other information. Nevertheless, a basic knowledge on where and how to find deeper or more detailed information is quite useful. Due to their complex nature, comprehensive searches (e.g., for processes or patents) are not recommended for beginners. However, most local (in-house), online, and CD-ROM databases provide extensive tutorials and help functions that are specific to the database, and that give a substantial introduction into database searching. 

A somewhat dilferent way to define a molecule is as a simplified molecular input line entry specification (SMILES) structure. It is a way of writing a single text string that defines the atoms and connectivity. It does not define the exact bond lengths, and so forth. Valid SMILES structures for ethane are CC, C2, and H3C-CH3. SMILES is used because it is a very convenient way to describe molecular geometry when large databases of compounds must be maintained. There is also a very minimal version for organic molecules called SSMILES. 

To ensure microbial strains are viable and pure a suite of morphological, biochemical, and cytochemical tests are used to confirm characteristics specific to their taxons. A number of commercially available rapid identification kits are also employed for some common genera. In addition to these taxon specific tests, many of the cultures are tested for their fatty acid methyl ester (FAME) profiles using the commercial MIDI system. The FAME profiles can be compared to the MIDI database for species identification/confirmation purposes. The Biolog system, which yields a metabolic fingerprint of an organism, is another alternative for rapid identification. 

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