Interpretive search system

When the unknown compoimd is not contained in the spectral library then prue identification methods are less useful. For unknown unknowns interpretive search systems or classification methods are required to obtain structural information that can be used for constructing molecular structure candidates. Such candidates are usually created manually by applying spectroscopic-chemical knowledge and intuition. A serious drawback of this strategy is that the solution is rarely complete and the procedure hardly can be documented or verified. 

T. L. Clerc, in Computer-Enhanced Analytical Spectroscopy, H. L. C. Meuzelaar, T.L. Isenhour (Eds.), Plenum Press, New York, 1987, pp. 145-162. Automated spectra interpretation and library search systems. 

In this chapter, we will discuss the present status of CHIRBASE and describe the various ways in which two (2D) or three-dimensional (3D) chemical structure queries can be built and submitted to the searching system. In particular, the ability of this information system to locate and display neighboring compounds in which specified molecular fragments or partial structures are attached is one of the most important features because this is precisely the type of query that chemists are inclined to express and interpret the answers. Another aspect of the project has been concerned with the interdisciplinary use of CHIRBASE. We have attempted to produce a series of interactive tools that are designed to help the specialists or novices from different fields who have no particular expertise in chiral chromatography or in searching a chemical database. 

For over a decade, a number of research teams have pursued the automation of this last, interpretative stage of the analytical spectroscopic process. There are two general ways of approaching this problem by using library searching systems or artificial intelligence systems (pattern recognition and expert systems) which are commented on below. 

Two methods are commonly applied for library searches. Identity or retrieval searches assume that the spectrum of the unknown compound is present in the reference library, and only experimental variability prevents a perfect match of the unknown and reference spectra. When no similar spectra are retrieved the only information provided is that the unknown spectrum is not in the library. Similarity or interpretive searches assume that the reference library does not contain a spectrum of the unknown compound, and are designed to produce structural information from which identity might be inferred. Interpretive methods typically employ a predetermined set of spectral features, designed to correlate with the presence of chemical substructures. Searching identifies the library spectra that have features most similar to those of the unknown spectrum. The frequency of occurrence of a substructure in the hit list is used to estimate the probability that it is present in the unknown compound. Two well-developed interpretative search algorithms are SISCOM (Search of Identical and Similar Compounds) and STIRS (the Self-Training Interpretive and Retrieval System) [174-177]. Normally a retrieval search is performed first, and when the results are inconclusive, an interpretive search is implemented. In both cases, success depends on the availability of comprehensive libraries of high-quality reference spectra [178]. 

Whatever algorithms are used, the usefulness of any substructure search system is limited by the types of query which it is possible to put to it, and the interpretation placed on them. 

Additional application of chemical knowledge to the selection of features or to the classifier construction has improved the classification results C1933. A comparison between pattern recognition methods and a sophisticated interpretative library search system for mass spectra ( STIRS C39, 4221) has indicated some superiority of the STIRS-system C172, 202, 3321. A decision tree pattern recognition was recommended by Neisel et. al. C2051 as a supplement to library search. 

The best worldwide performance has been claimed for more than one commercial MS database system. However, more neutral observers state that automated spectra interpretation systems have a rather limited scope. Spectra library search systems are now widely used in MS laboratories and do a good job with routine problems. They are not so useful with complex problems or if the unknown is not contained in the library however, cvurent research promises considerable improvements of these methods in the future. The routine application of library... 

Adams MJ (1995) Chemometrics in Analytical Spectroscopy. Cambridge The Royal Society of Chemistry. Clerc JT (1987) Automated spectra interpretation and library search systems. In Meuzelaar HLC and Isenhour TL (eds) Computer Enhanced Analytical Spectroscopy, Vol 1, pp 145-162. New York Plenum Press. 

In this presentation we will discuss the practical aspects of computer based search systems. Examples will be included from a commercial search program that incorporates a computer based interpretation. 

Many of the topics discussed so far are critical for successful results from most search systems. There is an additional step that can be taken to improve the quality of a search and that is to apply a spectrum interpretation as a pre-filter. At the beginning of this article we discussed the role of the spectroscopist. It would be very time consuming if the spectroscopist blindly sorted through reference spectra without any preconceived notion of the basic functionality of the unknown sample. Typically, functional groups are assigned from a knowledge of group frequencies. These... 

The purpose of this article has been to demonstrate the practical application of computer based search systems to common analytical problems. In many cases it is possible for the computer to perform the same role as the spectroscopist. This is achieved by the combination of a computer based interpretation with a flexible search program. The main advantages of this type of system are ... 

Woodruff and co-workers introduced the expert system PAIRS [67], a program that is able to analyze IR spectra in the same manner as a spectroscopist would. Chalmers and co-workers [68] used an approach for automated interpretation of Fourier Transform Raman spectra of complex polymers. Andreev and Argirov developed the expert system EXPIRS [69] for the interpretation of IR spectra. EXPIRS provides a hierarchical organization of the characteristic groups that are recognized by peak detection in discrete ames. Penchev et al. [70] recently introduced a computer system that performs searches in spectral libraries and systematic analysis of mixture spectra. It is able to classify IR spectra with the aid of linear discriminant analysis, artificial neural networks, and the method of fe-nearest neighbors. 

These include identification of process equipment and instruments, interpretation of the meaning of their values and trends, navigation through different VDU pages by means of a selection menu, etc. The common feature of these tasks is handling the display system to search and locate relevant process data. In this respect, "classical" ergonomics checklists (see Chapter 4) are very useful in facilitating performance of such tasks. 

A cmcial feature of the search for P,T-odd effects in atoms and molecules is that in order to interpret the measured data in terms of fundamental constants of these interaction, one must calculate specific properties of the systems to establish a connection between the measured data and studied fundamental constants. These properties are described by operators that are prominent in the nuclear region they cannot be measured, and their theoretical study is a non-trivial task. 

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