Feature based fuzzy matching of 2D gel electrophoresis images

Automatic alignment (matching) of two-dimensional gel electrophoresis images is of primary interest in the evolving field of proteomics. In the present study, feature-based matching techniques, in their classical and robust versions, are described, and an automatic method of fuzzy alignment (FA) is introduced. This method allows automatic matching of two gel images with different numbers of features with unknown correspondence. Performance of FA is tested on simulated and real data sets.     

Optimization of analytical information

Analytical chemists need formal strategies for optimal decision making at all levels of analytical chemistry: laboratory organization, analytical method design and selection, data interpretation.     

Expert system for precision testing in validation of liquid chromatographic methods

After a liquid chromatographic method has been developed, it must be validated to establish its limitations in daily use. Method validation is becoming increasingly important as stricter rules are applied by regulatory authorities. Precision testing is a vital step in this validation; both intralaboratory testing and interlaboratory testing are needed. In an intralaboratory test, repeatability and ruggedness tests are usually done. Expert systems are available for both tests. Here they are integrated to form an intralaboratory precision-testing expert system; special integration architecture is described. Important features of the integrated system are a supervisor containing planning knowledge about the tests and a common data structure containing all the objects necessary for an expert system in this area.     

Digital simulation as an aid to sample scheduling in a routine laboratory for liquid chromatography

A computer model is described to aid decision-making in a routine laboratory for liquid chromatography. The managerial demand was to reduce the delay times of the samples in the laboratory despite an increasing sample input. Knowledge derived from records on the laboratory and from the experience of the laboratory staff is used to develop a simulation model of the laboratory. The model is applied to study the effects of several factors on the performance of the laboratory in order to trace the bottlenecks.     

Data handling in HPLC-diode array UV-spectrometry

Summary The mathematical resolution of overlapped chromatographic peaks obtained in HPLC with a diode array UV detector has received considerable attention recently. The purpose of the proposed methods is the quantitation and identification of unknown solutes in complex mixtures by an efficient use of all available data. Basically two approaches have been proposed: the first one resolves the concentration profiles and calculates the pure spectra by applying a minimal number of assumptions, which is denoted self-modeling-curve resolution. The second one is based on a match of pure spectra available in a spectral library with the measured mixture spectra. In this paper both approaches are evaluated with respect to their performance to provide the pure spectra and an accurate quantitation of the concentrations.     

Multicomponent self-modelling curve resolution in high-performance liquid chromatography by iterative target transformation analysis

Iterative target transformation factor analysis can provide a method for resolving elution profiles consisting of any number of compounds. The results obtained for 3-component resolution are consistent with the results obtained with conventional methods of curve resolution. The same restrictions with regard to overlap and relative signal heights of the compounds seem to apply to the conventional method of curve resolution and the proposed method. The method is tested on data from high-performance liquid chromatography with a diode-array detector obtained for polynuclear aromatic hydrocarbons and for proteins.     

Digital simulation of the effect of dispatching rules on the performance of a routine laboratory for structural analysis

Several output characteristics of a laboratory for structural analysis are shown to be identical with the output of a model of that laboratory, e.g. the histograms of the input and output density (samples/day), the histograms of the number of samples present in the laboratory, the histograms of the delays and several cross-correlations. The effect of various strategies concerning priorities between various groups of samples is forecast, e.g. samples with a different expected analysis time, samples from various sources, samples with a different history in the laboratory. The effects of the introduction of an adaptable routing procedure, several technician assignment decisions and strategies on the termination of the analysis are simulated.