Bio-medical Ontologies Maintenance and Change Management

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330 M.T. Hoque, M. Chetty, and A. Sattar thereby increasing the number of collisions [3, 57]. To solve, alternate operators and move sets have also been applied [75]. An operator that is able to move the intended portion of the converging conformation with a predefined target, while concomitantly having minimal impact on the stable portion, exhibits considerable promise. One such operator, short pull move, or pull move was proposed by Lesh in the square 2D lattice model [75], which subsequently extended by Hoque et al. [3], with the introduction of the tilt move, which is applicable when other moves fail due to congestion. The tilt move however can disturb the stability more than the pull move. A selective implementation of the move sets based on current scenario could represent a powerful combination such as for instance, firstly attempting a diagonal move [3] and if this cannot be performed to reach a predefined goal then next applying a pull move and then a tilt move if the pull move perchance fails. Fig. 15 describes these moves in further detail. Lesh’s experiment demonstrates the superior performance in achieving the minimum energy conformation for longer sequences using the pull move in moving (a) (b) (c) Fig. 15. Various move operators (a) if ‘D’ is free, then ‘B’ can be move to ‘D’ via a diagonal move. (b) Before and after applying pull move is displayed. In first case ‘B’ can be pulled to ‘B´’ if ‘C´’ is free or ‘C’ is already at the position of ‘C´’ and the rest of the chain upto one end can be pulled until a valid conformation is reached. (c) Tilt move, ‘C’ and ‘D’ can be moved to ‘C´’ and ‘D´’ respectively and pull will propagate towards both ends. (a) (b) (c) (d) Fig. 16. The subsequence -123- in (a) need to remap to sub-conformation corresponds to – HPPH-. If the position 2′ is free then 2 can be placed at 2′ and a pull (indicated in (a)) applied towards the higher indexed end. The pull moves 3 to 2, 4 to 3 and 5 to 4 and then finds a valid conformation without pulling further leaving (b). The |fitness| in (b) is increased by 1. In (b) assume, 4′ and 5′ are free positions and the segment 3 to 6 can be recognized as –PHHP-. To enforce a mapping to highly probable sub-conformation, 4 and 5 can be shifted to 4′ and 5′ respectively applying a pull move which results (c). In (c), 8 can pass through position 9, 10, 11 and results (d) and increases |fitness| by 1 further. The position of H-Core centre (HCC) (‘ ’) is the arithmetic mean of the coordinates of all Hs.
Genetic Algorithm in Ab Initio Protein Structure Prediction 331 (a) (b) Fig. 17. Metaphoric HP folding kernels for (a) Cube 3D Lattice (b) 3D FCC lattice (a) (b) (c) (d) (e) Fig. 18. Potential sub-conformation in 3D space for the subsequence. Sub-conformation in (a) relates to –HPH- ( 1 S p ), (b) relates to –PHP- ( 1 S H ) and (c) related to -HPPH- ( 2 S P ). Further, both (d) and (e) relate to -PHHP- ( 2 SH ). Symbol ●, ○ and , respectively indicate an H, a P and the approximate position of HCC. phonotypically compact conformation, but it also provides lessons that random application of the move can consume significant computational resources. Hoque et al, has subsequently proven that incorporating domain specific knowledge [3, 80−82] with the move and their combinations afford considerable promise. As illustrated in Fig. 16, the pull move in both 2D and 3D FCC model helps to improve the fitness. Furthermore, as the parity problem is absent in the FCC model, the pull move does not need to be moved diagonally [81, 82] to start as in an ordinary pull because with more neighbours, the model is likely to get a valid conformation without the need to propagate the pull often upon the terminal residue. Further, Hoque et al. [3, 80−82] conceptualised the folded protein as a threelayered kernel (Fig. 17). The inner kernel, called the H-Core, is assumed compact and mainly formed of Hs while the outer kernel consists mostly of Ps. The H-Core [83] Centre is named HCC. The composite thin layer between the two kernels consists of those Hs that are covalent-bonded with Ps and is referred to as the HPmixed-layer. To integrate domain knowledge, Hoque et al, showed that the optimal core for a square 2D [3], cube 3D [80], 2D FCC [81] and 3D FCC [82] lattice are square, cube and regular hexagon respectively, which concludes the optimal core that maximizes the |fitness| can be predicted based upon the properties and dimension of the model. To form the cavity of H-Core Hoque et al. further introduced, motifs or sub-conformations based approach which are highly
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Amandeep S. Sidhu and Tharam S. Dil
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Amandeep S. Sidhu and Tharam S. Dil
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Preface The molecular biology commu
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Preface VII biomedical systems, and
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X Contents Mining Clinical, Immunol
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2 A.S. Sidhu, M. Bellgard, and T.S.
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Towards Bioinformatics Resourceomes
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2 The New Waves Towards Bioinformat
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2.4 Semantic Web Towards Bioinforma
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A Summary of Genomic Databases: Ove
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Appendix A Summary of Genomic Datab
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Protein Data Integration Problem Am
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Protein Data Integration Problem 57
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Fig. 3. Class Hierarchy of Protein
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Bio-medical Ontologies Maintenance
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TextToOnto (Maedche and Volz 2001)
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Extraction of Constraints from Biol
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Classifying Patterns in Bioinformat
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Mining Clinical, Immunological, and
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Substructure Analysis of Metabolic
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entry compound relation subtype com
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Running Time 4500 4000 3500 3000 25
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6 Conclusion Substructure Analysis
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266 J.Y. Chen, S. Taduri, and F. Ll
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Bio-medical Ontologies Maintenance and Change Management

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