Artificial classification systems

Selected entries from Methods in Enzymology [vol, page(s)] Databases and Resources Information services of European Bioinformatics Institute, 266, 3 TDB new databases for biological discovery, 266, 27 PIR-international protein sequence database, 266, 41 superfamily classification in PIR-international protein sequence database, 266, 59 gene classification artificial neural system, 266, 71 blocks database and its applications, 266, 88 indexing and using sequence databases, 266, 105 SRS information retrieval system for molecular biology data banks, 266, 114. 

Wu, C. H. (1996). Gene Classification Artificial Neural System. Methods Enzymol 266,71-88. 

The artificial intelligence systems to which sensor arrays are coupled supply the closest likeness to the human olfactory system. Some of the recent theories on olfaction require that the human nose has only relatively few types of receptor, each with low specificity. The activation of differing patterns of these receptors supplies the brain with sufficient information for an odour to be described, if not recognized. As a consequence of this belief, the volatile chemical-sensing systems commercially available only contain from 6 to 32 sensors, each having relatively low specificity. Statistical methods such as principal component analysis, canonical discriminant analysis and Euclidian distances are used for mapping or linked to artificial neural nets as an aid to classification of the odour fingerprints . 

Udelhoven T, Naumann D, Schmitt J. Development of a hierarchical classification system with artificial neural networks and FT-IR spectra for the identification of bacteria. Appl Spectrosc. 2000 54(10) 1471-9... 

MSHA s 1988 Coal Accident Analysis and Problem Identification Instruction Guide shows how a system of classification designed to collect premium data can become an artificial template that structures not only the activity of the inspection but also the conclusions that inspectors can draw from their data. The Instruction Guide provides a set of checklists, tally sheets, and planned inquiry sheets to help inspectors categorize accidents. The classification system in the Physical Barrier Analysis Matrix (Fig. 3.1) seems to support the conclusion that physical barriers are either not possible or practical in most of the cases reported on the form—a conclusion that might exempt management from responsibility for protecting workers. Because data from such an analysis directly affects policy and procedures, classification systems can have... 

The pragmatic compromise that had prevailed since the 1840s was not displaced by Mendeleev s periodic system. Hybrid natural/artificial classifications were still largely used in French chemistry textbooks up to the first decades of the twentieth century, while the ideal natural classification remained in a far distant future (Figure 5.2). While this general attitude may partially explain why most chemistry authors obviated Mendeleev s ideas in their textbooks, it nevertheless raises a question How is it that a few authors paid attention to an imperfect and unfeasible classificatory system ... 

Thus, the periodic system was introduced as part and parcel of a French battle for the atomic theory. When the atomic weight notation and system supported by Wurtz became compulsory in the official curricula for secondary education, a new generation of textbook authors clearly announced the adoption of the atomic theory in their titles. However, only a few of them included the chemical properties observed by a Russian chemist in the package of the atomic theory. And even in their secondary school and university textbooks, the old hybrid natural/artificial classification proved extremely resilient. 

For homogeneous NDT data and repeatable inspection conditions successful automated interpretation systems can relatively easily be developed. They usually use standard techniques from statistical classification or artificial intelligence. Design of successful automated interpretation systems for heterogeneous data coming form non-repeatable, small volume inspections with little a-priori information about the pieces or constructions to be inspected is far more difficult. This paper presents an approach which can be used to develop such systems. 

M. Mulholland, D.B. Hibbert, P.R. Haddad and P. Parslov, A comparison of classification in artificial intelligence, induction versus a self-organising neural networks. Chemom. Intell. Lab. Systems, 30 (1995) 117-128. 

Such an inter-type difference will not be utilized in this book, mainly because it complicates the classification and is not necessary as tbe focus is placed on the substrates and the products. The argument is also valid for enzymatic transformations [12d, 14], where one enzymatic system with one enzyme or different independent enzymatic systems with one or more enzymes may be used. In Nature, as well as in several artificial enzymatic domino reactions, a mixture of different enzymes catalyzing independent cycles is employed. 

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