Matches function extension function

Another SQL extension is needed that can understand the molecular structural nature of the SMILES string and treat it like more than just a text string. Suppose there is a function matches (A,B) that returns true when structure A contains structure B. Both these structures could be represented as SMILES and the matches function itself would understand the molecular nature properly. Then matches( C( N)S, C N ) would be true as would matchesCSC N, N C ), as intended. The matches function can be used to find all cyano-containing structures in a table using an SQL clause such as where matches (cansmi, C N )-... 

Another useful SQF extension function is list matches (A,B). This returns an array of integers telling which atoms in SMILES A were matched by SMARTS B. For example, list matches( CC(O)C, C ) returns the array 1,2,4. This list can be used for additional processing of the matches SMITES, for example, to color the matched atoms in a drawing or viewing application. 

Suppose it is decided that the valence 5, noncharge-separated representation of the nitro group is to be used throughout the database. The SMIRKS [0 2]=[N+ 1][0- 3] [0 2]=[N+0 1]=[0+0 3], when applied to any charge-separated nitro group will transform it into the proper form. This is accomplished by creating another new SQL function, xform(smiles, smarts). As with the cansmiles and matches functions, this is an extension to standard SQL. Some form of this transformation function is... 

The previous section shows how molecular structures stored in an RDBMS can be made available to client programs that traditionally read molecular structure files. The advantage of storing molecular structures in an RDBMS is that the information can be used from within the database, as well as by external clients. For example, it would be possible to search a table of molecular structures for three-dimensional overlap, much like it might be searched for substructure match. Of course, such search functions need to be written and installed as extensions to an RDBMS, just like the matches functions was done for substructure searches. This section shows some possible ways this might be accomplished. 

However, it has turned out that the most accurate way of fixing these parameters is through matching of simulated phase equilibria to those derived from experiment.33 As a final step, the potential, regardless of its source, should be validated through extensive comparison with available experimental data for structural, thermodynamic, and dynamic properties obtained from simulations of the material of interest, closely related materials, and model compounds used in the parameterization. The importance of potential function validation in simulation of real materials cannot be overemphasized. 

Extension of the classical Landau-Ginzburg expansion to incorporate nonclassical critical fluctuations and to yield detailed crossover functions were first presented by Nicoll and coworkers [313, 314] and later extended by Chen et al. [315, 316]. These extensions match Ginzburg theory to RG theory, and thus interpolate between the lower-order terms of the Wegner expansion at T -C Afa and mean-field behavior at f Nci-... 

But experiments to resolve the fine structure of the Balmer lines were difficult as you all know, resolution was impeded by the Doppler broadening of components. So ionized helium comes into the picture, because, as Sommerfeld s formula predicted, fine structure intervals are a function of (aZ)2, so in helium they are of order four times as wide as in hydrogen and one has more chance of resolving the Doppler-broadened lines. So PASCHEN [40], in 1916. undertook an extensive study of the He+ lines and in particular, 4686 A (n = 4->3). Fine structure, indeed, was found and matched against Sommerfeld s formula. The measurements were used to determine a value of a. But the structure did not really match the theory in that the quantum numbers bore no imprint of electron spin, so even the orbital properties - which dominated the intensity rules based on a correspondence with classical radiation theory - were wrongly associated with components, and the value of a derived from this first study was later abandoned. 

The mouse Dtnbpl transcript identified as a on AceView is predicted to encode a protein of 408 aa, which is 56 aa longer than the largest mouse dysbindin-1A isoform reported in the literature (i.e., the 352 aa isoform of Benson et al., 2001). If we accept the first ATG in transcript a as the start codon, the predicted protein matches the 352 aa isoform. AceView instead lists the longer possibility for two reasons. Near the 5 end of the transcript is a less common start codon sequence (CTG). Between the 5 end and the first ATG sequence are 168 nucleotides potentially encoding an arginine-proline rich N-terminal extension that may serve as a nuclear localization signal of functional interest. Indeed, the 408 aa variant of dysbindin-1 A has been predicted in mouse undifferentiated limb mesenchyme (NCBI accession no. AAH48682). But it is not predicted elsewhere. In most tissues, then, transcript a is probably translated as the 352 aa isoform. 

There are several allotropic forms of elemental phosphorus, the most common being the white, red, and black forms. Red phosphorus, which itself includes several forms, is obtained by heating the white form at 400 °C for several hours. An amorphous red form may also be prepared by subjecting white phosphorus to ultraviolet radiation. In the thermal transformation, several substances function as catalysts (e.g., iodine, sodium, and sulfur). Black phosphorus appears to consist of four different forms. These are obtained by the application of heat and pressure to the white form. The major uses of elemental phosphorus involve the production of phosphoric acid and other chemicals. Red phosphorus is used in making matches, and white phosphorus has had extensive use in making incendiary devices. Several of the important classes of phosphorus compounds will be discussed in later sections. 

---