Multidimensional databases

The described computational tools provide interactive, fast, and flexible data visualizations of chemical data that help and even enhance the human thought processes. However, visualization alone is often inadequate when multiple data points must be considered. A number of data mining methods that seek to identify significant relationships in large multidimensional databases are now being used for library design. 

Development of multidimension pathway databases Current database tools do not encompass the true complexities of plants. In this regard, multidimensional databases need to be developed to integrate allelic variation with temporal, developmental, tissue-specific, and biotic and abiotic influences on pathway flux and pigment accumulation. 

Multidimensional Database. A relational database in which multiple general types of data are stored, indexed, and cross-referenced, for use by several different groups. In chemistry, an example would be a database containing reactions, 2D structures, perhaps generic structures or libraries, and 3D models. Such a database would be used by synthetic, chemical informatic, and molecular modeling scientists. A data warehouse is often a multidimensional database, whereas a data mart is usually single-dimensional. 

The second method for mixture analysis is the use of specialized software together with spectral databases. We have developed a mixture analysis program AMIX for one- and multidimensional spectra. The most important present applications are the field of combinatorial chemistry and toxicity screening of medical preparations in the pharmaceutical industry. An important medical application is screening of newborn infants for inborn metabolic errors. 

Due to the ready accessibility of SH2 domains by molecular biology techniques, numerous experimentally determined 3D structures of SH2 domains derived by X-ray crystallography as well as heteronuclear multidimensional NMR spectroscopy are known today. The current version of the protein structure database, accessible to the scientific community by, e.g., the Internet (http //www.rcsb.org/pdb/) contains around 80 entries of SH2 domain structures and complexes thereof. Today, the SH2 domain structures of Hck [62], Src [63-66], Abl [67], Grb2 [68-71], Syp [72], PLCy [73], Fyn [74], SAP [75], Lck [76,77], the C- and N-terminal SH2 domain ofp85a [78-80], and of the tandem SH2 domains Syk [81,82], ZAP70 [83,84], and SHP-2 [85] are determined. All SH2 domains display a conserved 3D structure as can be expected from multiple sequence alignments (Fig. 4). The common structural fold consists of a central three-stranded antiparallel ft sheet that is occasionally extended by one to three additional short strands (Fig. 5). This central ft sheet forms the spine of the domain which is flanked on both sides by regular a helices [49, 50,60]. 

In our laboratory, we have developed a novel MALDI-MS based assay in combination with separation techniques to rapidly identify and confirm the presence of viral proteins (immature or mature) and impurities in the rAd vector [138], The approach combines powerful multidimensional analytical techniques to fully characterize viral proteins, including RP-HPLC, SDS-PAGE, MALDI-MS, MS/MS, and database searching methods (Figure 19-24). This assay involves dissociation/separation of intact viruses by RP-HPLC, separation of the SDS-dissociated viruses by SDS-PAGE, and enzymatic digestion of the dissociated viral proteins from the RP-HPLC fractions and the gel bands, followed by MALDI-MS, MALDLpost source decay (PSD) studies, and database search. 

Figure 9.16. Star schema design of a chemical data warehouse. The central source table allows access to the Extemal-IDof every molecule, arranged by source database. These External-ID values can be used to build multidimensional views of the data. For example, to see all the reactions with products that can be found in source database ACD, one would combine data from the source dictionary table (Source ID for database ACD), the reactions table (StructJD, and Role), and moltable (Struct ID) table, using identifiers (Extemal-ID)from the central source table.

Sheng S, Chen D, van Eyk JE (2006) Multidimensional liquid chromatography separadon of intact proteins by chromatographic focusing and reversed phase of the human serum proteome Optimizadon and protein database. Mol Cell Proteomics 5 26-34. 

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