Pattern recognition programs

Step 8. Spectra classified using an artificial neural network pattern recognition program. (This program is enabled on a parallel-distributed network of several personal computers [PCs] that facilitates optimization of neural network architecture). 

Because protein ROA spectra contain bands characteristic of loops and turns in addition to bands characteristic of secondary structure, they should provide information on the overall three-dimensional solution structure. We are developing a pattern recognition program, based on principal component analysis (PCA), to identify protein folds from ROA spectral band patterns (Blanch etal., 2002b). The method is similar to one developed for the determination of the structure of proteins from VCD (Pancoska etal., 1991) and UVCD (Venyaminov and Yang, 1996) spectra, but is expected to provide enhanced discrimination between different structural types since protein ROA spectra contain many more structure-sensitive bands than do either VCD or UVCD. From the ROA spectral data, the PCA program calculates a set of subspectra that serve as basis functions, the algebraic combination of which with appropriate expansion coefficients can be used to reconstruct any member of the... 

Software Availability. The SIMCA software is available in two forms, both developed by Wold (25) 1) an interactive, Fortran version which runs on Control Data Corporation (CDC) machines. The second set of programs are an interactive microcomputer version, SIMCA-3B, are available from Principal Data Components, 2505 Shepard Blvd., Columbia, MO 65201. The SIMCA-3B pattern recognition programs includes the CPLS-2 program used for PLS analysis and are available for CP/M (Digital Research, Pacific Grove, CA) and MS-DOS (Microsoft Corporation, Bellueve, WA) for 8088 or 80 86 based microcomputers. 

To enable reflectometry to provide accurate, reproducible, and efficient measurements, several factors must be considered. Choice of the substrate material, substrate modeling, number of measurements per wafer, choice of the measurement patterns, and the setup of the pattern recognition program are all critical to the measurement process, as discussed in the following. 

One determines the overall reaction by using some of the many tools of chemical analysis. Coulometeiy, gas chromatography, mass spectroscopy, and, in complex cases, computerized pattern-recognition programs applied to GC-MS data (see Section 7.5.19) are the typical tools used in determining the overall reaction. The current efficiency for the reaction concerned is important here and may vaty with potential. 

Isoflavone derivatives along with nonvolatile components in soy sauce were also analyzed by gradient reversed-phase HPLC. This HPLC profile of soy sauce was further utilized by a pattern recognition program to understand the quality differences of soy sauces (132), and three isoflavone derivatives (esters of tartaric acid with daidzein, genistein, and 8-hydroxygenistein) were found to contribute significantly to the differentiation in fermented soy sauce. Fermented... 

Pattern Recognition Analysis. A set of interactive pattern recognition programs have been interfaced to the ADAPT system. 

Several pattern recognition programs have been applied by WegscheideV et. al. C3261 to the interpretation of a set of trace element concentrations in groundwater. The data set consisted of 149 samples with up to ten measurements made on each sample. Four different origins of these samples have been successfully visualized by display methods. 

R. KOWALSKI B.R. ARTHUR (PATTERN RECOGNITION PROGRAM), AVAILABLE FROM KOWALSKI B.R., LAB. FOR CHEMOMETRICS, DEPT. OF CHEMISTRY, BG-10,... 

A pattern recognition program was used to determine G, S and G M phase. 

Cell cycle analysis of peritoneal EA cells was determined with a cell sorter utilizing a pattern recognition program. 

Tel. 206-441-4696, fax 206-441-0841, e-mail infomtrx halcyon.com Chemometric analysis based in part on the ARTHUR pattern recognition program. InStep for routine application of statistical models. EinSight for multivariate and visual data exploration. PCs (DOS). 

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