Structure knowledge-based

Duncan, Elizabeth B. Structuring knowledge bases for designers of learning materials. In Hypermedia, Vol.l, 1, (20-33), London Taylor Graham, 1989. 

Ryan, G. (1999). Ensuring that students develop an adequate, and well-structured, knowledge base. In D. Bond G. Eeletti (Eds.), The challenge of problem-based learning (2nd ed., pp. 125-136). London Kogan Page. 

An excessive amount of material in the curriculum Relatively high class contact hours A lack of opportunity to pursue subjects in depth A lack of choice of subjects and methods of study Threatening and anxiety-provoking assessment A competitive environment Student perceptions that deep learning is required A motivational context A weU-structured knowledge base Learner activity and choices Assessment based on application to new situations Interaction with others and collaboration... 

The design process is essentially structured around a search of the defined solution spaces to identify established practices and design embodiments and of finding ways of combining these to produce a new or improved product or outcome. Increasingly, methods based around the use of expert systems and structured knowledge bases are providing the means by... 

The classical computer tomography (CT), including the medical one, has already been demonstrated its efficiency in many practical applications. At the same time, the request of the all-round survey of the object, which is usually unattainable, makes it important to find alternative approaches with less rigid restrictions to the number of projections and accessible views for observation. In the last time, it was understood that one effective way to withstand the extreme lack of data is to introduce a priori knowledge based upon classical inverse theory (including Maximum Entropy Method (MEM)) of the solution of ill-posed problems [1-6]. As shown in [6] for objects with binary structure, the necessary number of projections to get the quality of image restoration compared to that of CT using multistep reconstruction (MSR) method did not exceed seven and eould be reduced even further. 

Correlations between structure and mass spectra were established on the basis of multivariate analysis of the spectra, database searching, or the development of knowledge-based systems, some including explicit management of chemical reactions. 

The most recent version of EROS has a clearcut separation of the system proper, which performs all the manipulations on chemical structures and reactions, from the knowledge base, which defines the scope of it.s application (Figure 10.3-7). 

Ithough knowledge-based potentials are most popular, it is also possible to use other types potential function. Some of these are more firmly rooted in the fundamental physics of iteratomic interactions whereas others do not necessarily have any physical interpretation all but are able to discriminate the correct fold from decoy structures. These decoy ructures are generated so as to satisfy the basic principles of protein structure such as a ose-packed, hydrophobic core [Park and Levitt 1996]. The fold library is also clearly nportant in threading. For practical purposes the library should obviously not be too irge, but it should be as representative of the different protein folds as possible. To erive a fold database one would typically first use a relatively fast sequence comparison lethod in conjunction with cluster analysis to identify families of homologues, which are ssumed to have the same fold. A sequence identity threshold of about 30% is commonly... 

Barton G J 1998. Protein Sequence Aligrunent Techniques. Acta Crystallographica 054 1139-1146. Blundell T L, B L Sibanda, M J E Sterbnerg and J M Thornton. Knowledge-based Prediction of Prote Structures and the Design of Novel Molecules. Nature 326 347-352. 

M J1990. Calculation of Conformational Ensembles from Potentials of Mean Force. An Approach o the Knowledge-Based Prediction of Local Structures in Globular Proteins. Journal of Molecular Siology 213 859-883. 

TL Blundell, BL Sibanda, MJE Sternberg, JM Thornton. Knowledge-based prediction of protein structures and the design of novel molecules. Nature 326 347-352, 1987. 

MJ Sutcliffe, I Haneef, D Carney, TL Blundell. Knowledge based modelling of homologous proteins. Part I Three dimensional frameworks derived from the simultaneous superposition of multiple structures. Protein Eng 1 377-384, 1987. 

MI Sippl. Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures m globular proteins. I Mol Biol 213 859-883, 1990. 

For each of the 500 or so different domain structures that have so far been observed, we might at best know about a dozen of these different possible sequences. It is not trivial to recognize the general sequence patterns that are common to specific domain structures from such a limited knowledge base. 

Natural mutation of amino acids in the core of a protein can stabilize the same fold with different complementary amino acid types, but they can also cause a different fold of that particular portion. If the sequence identity is lower than 30% it is much more difficult to identify a homologous structure. Other strategies like secondary structure predictions combined with knowledge-based rules about reciprocal exchange of residues are necessary. If there is a reliable assumption for common fold then it is possible to identify intra- and intermolecular interacting residues by search for correlated complementary mutations of residues by correlated mutation analysis, CMA (see e.g., http //www.fmp-berlin.de/SSFA). 

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