List matches function

Some of the more advanced methods described in this book require a more specific use of the RDBMS. The choice made for this book is PostgreSQL. In cases where a particular feature of PostgreSQL is used, a note is added to alert the reader. For example, the array data type in SQL2003 is implemented in PostgreSQL very differently than in Oracle. The list matches function described in a later chapter of this book returns an array of integers that denote which atoms in a structure match a substructure query. The integration of this function into SQL would be handled quite differently in PostgreSQL, Oracle and MySQL. 

Functional specification is derived from the user requirements specification and includes the description of the functionality that is needed to fulfill the requirements. It either may be a list of functions or may include proposals for user interfaces and describes the individual functionality in their context to match the operator s requirements. In the latter case, the corresponding document is often referred to as system specihcation, which may be created in addition to the functional specification. Which procedure is followed relies on the internal documentation standards of the development organization. 

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. 

The CHORD6 chemical cartridge is a commercial product from gNova, Inc. It is written using C functions and the OEChem toolkit from OpenEye. It provides the core functions discussed in this book, such as cansmiles, matches, count matches, list matches, smiles to molfile, molfile to smiles, and xform. CHORD makes it possible to efficiently process RDBMS tables containing many millions of chemical structures. 

Create Or Replace Function list matches(text, text, integer) Returns Text[] As EOPERL use Chemistry File SMILES use Chemistry File SMARTS use Chemistry Ring aromatize mol ... 

Convenience function to return first match Select list matches( 1, 2, 1) ... 

Create Or Replace Function frowns.list matches(smi Text, sma Text,... 

Create Or Replace Function openbabel.list matches(smi Text, sma Text, imatch Integer, istart Integer) Returns Integer ] As EOPY import openbabel obc = openbabel.OBConversion() mol = openbabel.OBMol() obc.SetlnFormat("smi") if obc.Readstring(mol, smi) ... 

Create Or Replace Function openbabel.list matches(Text, Text) Returns Integer ] As EOSQL ... 

Table I lists values of the CIE color-matching functions for 2° and 10° fields at 10-nm wavelength values. Tables for 1-nm wavelength values for 2° and 10° fields are available in Color Measurement, the second volume in the series Optical Radiation Measurements, edited by F. Grum and C. J. Bartleson.

Eortunately, a 3D model does not have to be absolutely perfect to be helpful in biology, as demonstrated by the applications listed above. However, the type of question that can be addressed with a particular model does depend on the model s accuracy. At the low end of the accuracy spectrum, there are models that are based on less than 25% sequence identity and have sometimes less than 50% of their atoms within 3.5 A of their correct positions. However, such models still have the correct fold, and even knowing only the fold of a protein is frequently sufficient to predict its approximate biochemical function. More specifically, only nine out of 80 fold families known in 1994 contained proteins (domains) that were not in the same functional class, although 32% of all protein structures belonged to one of the nine superfolds [229]. Models in this low range of accuracy combined with model evaluation can be used for confirming or rejecting a match between remotely related proteins [9,58]. 

Prosite is perhaps the best known of the domain databases (Hofmann et al., 1999). The Prosite database is a good source of high quality annotation for protein domain families. Prosite documentation includes a section on the functional meaning of a match to the entry and a list of example members of the family. Prosite documentation also includes literature references and cross links to other databases such as the PDB collection of protein structures (Bernstein et al., 1977). For each Prosite document, there is a Prosite pattern, profile, or both to detect the domain family. The profiles are the most sensitive detection method in Prosite. The Prosite profiles provide Zscores for matches allowing statistical evaluation of the match to a new protein. Profiles are now available for many of the common protein domains. Prosite profiles use the generalized profile software (Bucher et al., 1996). 

There are an infinite number of nonlinear functions that can be proposed, depending on the shape of the data. The most common functions used for regression in the region ofx > 0 include those listed in table 5.7. Some of the more popular functional forms are shown in figure 5.2. A function should be chosen with a shape that matches the general shape of the data. 

Machines are relatively easy to analyze because both their function and all of their parts, each nut and bolt, are known and can be listed. It is then simple to see if any given part is required for the function of the system. If a system requires several closely matched parts to function then it is irreducibly complex, and we can conclude that it was produced as an integrated unit. In principle, biological systems can also be analyzed in this manner, but only if all the parts of the system can be enumerated and a function recognized. 

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. 

All variables whose values are read in the always statement must appear in the event list (the parenthesized list following the symbol) otherwise the functionality of the synthesized netlist may not match that of the design model. Here is a simple example that illustrates this point. 

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