Bio-medical Ontologies Maintenance and Change Management

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The Minimal Model of Glucose Disappearance in Type I Diabetes 315 16. Lehmann, E.D., Deutsch, T.: A physiological model of glucose-insulin interaction in type 1 diabetes mellitus. J. Biomed. Eng. 14, 235–242 (1992) 17. Radziuk, J., McDonald, T., Rubentein, D., Dupre, J.: Initial splanchnic extraction of ingested glucose in normal man. Metabolism 27(6), 657–669 (1978) 18. Shichiri, M., Sakakida, M., Nishida, K., Shimoda, S.: Enhanced, simplified glucose sensors: long-term clinical application of wearable artificial pancreas. Artif. Organs 22(1), 32–42 (1998) 19. Willinska, M.E., Chassin, L.J., Schaller, H.C., Schaupp, L., Pieber, T.R., Hovorka, R.: Insulin kinetics in Type-1 diabetes: Continuous and bolus delivery of rapid acting insulin. IEEE. Trans. Biomed. Eng. 52(1), 3–12 (2005)
Genetic Algorithm in Ab Initio Protein Structure Prediction Using Low Resolution Model: A Review Md. Tamjidul Hoque 1 , Madhu Chetty 2 , and Abdul Sattar 1 1 IIIS, Griffith University, Nathan, QLD-4111, Australia 2 GSIT, Monash University, Churchill, VIC 3842, Australia Tamjidul.Hoque@gmail.com, Madhu.Chetty@infotech.monash.edu.au, a.sattar@griffith.edu.au Abstract. Proteins are sequences of amino acids bound into a linear chain that adopt a specific folded three-dimensional (3D) shape. This specific folded shape enables proteins to perform specific tasks. The protein structure prediction (PSP) by ab initio or de novo approach is promising amongst various available computational methods and can help to unravel the important relationship between sequence and its corresponding structure. This article presents the ab initio protein structure prediction as a conformational search problem in low resolution model using genetic algorithm. As a review, the essence of twin removal, intelligence in coding, the development and application of domain specific heuristics garnered from the properties of the resulting model and the protein core formation concept discussed are all highly relevant in attempting to secure the best solution. 1 Introduction Ab initio protein structure prediction (PSP) is an important and very challenging interdisciplinary problem encompassing biochemistry, biophysics, structural biology, molecular biology and computational biology to give just a couple of examples. Structure prediction, especially in revealing the relationship between sequences and protein folding is the key to combating many diseases and the development of several crucial biotechnological applications and the ab initio approach in this regard offers great hope for improving the human condition. More than half of the dry weight of a cell is made up of proteins of various shapes and sizes and protein’s specific folded three-dimensional (3D) shape (Fig. 1) enables it to perform specific tasks. From the computing point of view, the exciting investigations concerning proteins is not necessarily about these molecules carrying out vital tasks but mainly about the process of its acquiring various shapes, i.e. protein folding problem, which enable it to perform the specific tasks. To solve the PSP problem, among other approaches nondeterministic searching approach Genetic Algorithms are found promising [1, 2, 3]. On the other hand, to model and to handle the complexity of the protein folding the low resolution model found [4, 5, 6] to be effective exploring the vast and convoluted search space in a reasonable time A.S. Sidhu et al. (Eds.): Biomedical Data and Applications, SCI 224, pp. 317–342. springerlink.com © Springer-Verlag Berlin Heidelberg 2009
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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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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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Running Time 4500 4000 3500 3000 25
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