Integrating knowledge representation and quantitative modelling in physiology

Biotechnology Journal

Volumn 7, Issue 8, 2012, Pages 958-972

  de Bono, Bernard ^a,b,c   Hunter, Peter ^a,d  

^a UNIVERSITY OF AUCKLAND   (New Zealand)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

^c EUROPEAN BIOINFORMATICS INSTITUTE   (United Kingdom)

^d UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

Computational physiology; Medical biotechnology; Multiscale modelling; Personalized medicine; Physiome project

Indexed keywords

COMPUTATIONAL PHYSIOLOGY; MEDICAL BIOTECHNOLOGY; MULTI-SCALE MODELLING; PERSONALIZED MEDICINES; PHYSIOME;

ENCODING (SYMBOLS); GLUCOSE; HEALTH CARE; KNOWLEDGE REPRESENTATION; METADATA; PHYSIOLOGY; SEMANTICS; VIRTUAL REALITY; VISUALIZATION;

PHYSIOLOGICAL MODELS;

ARTICLE; HEALTH CARE SYSTEM; MEDICAL INFORMATION; PERSONALIZED MEDICINE; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS;

ARTIFICIAL INTELLIGENCE; BIOTECHNOLOGY; COMPUTATIONAL BIOLOGY; COMPUTER GRAPHICS; HUMANS; INDIVIDUALIZED MEDICINE; MODELS, BIOLOGICAL; PHYSIOLOGY;

EID: 84864818456     PISSN: 18606768     EISSN: 18607314     Source Type: Journal    
DOI: 10.1002/biot.201100304     Document Type: Article

References (46)

1. Wang, Y., Gjuvsland, A. B., Vik, J. O., Smith, N. P. et al., Parameters in dynamic models of complex traits are containers of missing heritability. PLoS Comput. Biol. 2012, 8, e1002459.
2. Bassingthwaighte, J. B., Strategies for the Physiome Project. Ann. Biomed. Eng. 2000, 28, 1043-1058.
3. Crampin, E., Smith, N., Hunter, P., Multiscale modelling and the IUPS Physiome Project. J. Mol. Histol. 2004, 35, 707-714.
4. Hunter, P. J., Borg, T. K., Integration from proteins to organs: The Physiome Project. Nat. Rev. Mol. Cell Biol. 2003, 4, 237-243.
5. Hunter, P. J., The IUPS physiome project: A framework for computational physiology. Prog. Biophys. Mol. Biol. 2004, 85, 551-569.
6. Hunter, P. J., Pullan, A. J., Smaill, B. H., Modeling total heart function. Annu. Rev. Biomed. Eng. 2003, 5, 147-177.
7. Tawhai MH, Multi-scale lung modeling. J. Appl. Physiol. 2011, 110, 1466-1472.
8. Nickerson, D. P., Terkildsen, J., Hamilton, K. L., Hunter, P. J., A tool for multi-scale modelling of the renal nephron. Interface Focus 2011, 1, 417-425.
9. de Bold, A. J., Thirty years of research on atrial natriuretic factor: Historical background and emerging concepts. Can. J. Physiol. Pharmacol. 2011, 89, 527-531.
10. Montoliu, C., Kosenko, E., Del Olmo, J. A., Serra, M. A. et al., Correlation of nitric oxide and atrial natriuretic peptide changes with altered cGMP homeostasis in liver cirrhosis. Liver Int. 2005, 25, 787-795.
11. Nannipieri, M., Seghieri, G., Catalano, C., Prontera, T. et al., Defective regulation and action of atrial natriuretic peptide in type 2 diabetes. Horm. Metab. Res. 2002, 34, 265-270.
12. Clerico, A., Iervasi, G., Alterations in metabolic clearance of atrial natriuretic peptides in heart failure: How do they relate to the resistance to atrial natriuretic peptides? J. Card. Fail. 1995, 1, 323-328.
13. Ni, X. P., Safai, M., Gardner, D. G., Humphreys, M. H., Increased cGMP phosphodiesterase activity mediates renal resistance to ANP in rats with bile duct ligation. Kidney Int. 2001, 59, 1264-1273.
14. Djousse, L., Hunt, S. C., Eckfeldt, J. H., Arnett, D. K. et al., Alcohol consumption and plasma atrial natriuretic peptide (from the HyperGEN study). Am. J. Cardiol. 2006, 98, 628-632.
15. Kovacs, G. L., Natriuretic peptides in alcohol withdrawal: Central and peripheral mechanisms. Curr. Med. Chem. 2003, 10, 2559-2576.
16. Mutschler, J., Bilbao, A., von der Goltz, C., Demiralay, C. et al., Augmented stress-induced alcohol drinking and withdrawal in mice lacking functional natriuretic peptide-A receptors. Alcohol Alcohol. 2010, 45, 13-16.
17. Levitt, M. D., Li, R., DeMaster, E. G., Elson, M. et al., Use of measurements of ethanol absorption from stomach and intestine to assess human ethanol metabolism. Am. J. Physiol. 1997, 273, G951-957.
18. Norberg, A., Gabrielsson, J., Jones, A. W., Hahn, R. G., Within- and between-subject variations in pharmacokinetic parameters of ethanol by analysis of breath, venous blood and urine. Br. J. Clin. Pharmacol. 2000, 49, 399-408.
19. Ting, J. W., Lautt, W. W., The effect of acute, chronic, and prenatal ethanol exposure on insulin sensitivity. Pharmacol. Ther. 2006, 111, 346-373.
20. +ATPase. Neuropsychopharmacol. 2010, 35, 1984-1996.
21. Tirapelli, L. F., Batalhão, M. E., Jacob-Ferreira, A. L., Tirapelli, D. P. et al., Chronic ethanol consumption induces histopathological changes and increases nitric oxide generation in the rat liver. Tissue Cell 2011, 43, 384-391.
22. Clark, S. J., Shojaee-Moradie, F., Croos, P., Seed, P. T. et al., Temporal changes in insulin sensitivity following the development of acute liver failure secondary to acetaminophen. Hepatology 2001, 34, 109-115.
23. Mather, A., Pollock, C., Glucose handling by the kidney. Kidney Int. Suppl 2011, 120, S1-6.
24. Leiter, L. A., From hyperglycemia to the risk of cardiovascular disease. Rev. Cardiovasc. Med. 2006, 7Suppl2, S3-9.
25. Macisaac, R. J., Jerums, G., Diabetic kidney disease with and without albuminuria. Curr. Opin. Nephrol. Hypertens. 2011, 20, 246-357.
26. Lelkes, E., Unsworth, B. R., Lelkes, P. I., Reactive oxygen species, apoptosis and altered NGF-induced signaling in PC12 pheochromocytoma cells cultured in elevated glucose: An in vitro cellular model for diabetic neuropathy. Neurotox. Res. 2001, 3, 189-203.
27. Najafian, B., Alpers, C. E., Fogo, A. B., Pathology of human diabetic nephropathy. Contrib. Nephrol. 2011, 170, 36-47.
28. van Deursen, R. W., Simoneau, G. G., Foot and ankle sensory neuropathy, proprioception, and postural stability. J. Orthop. Sports Phys. Ther. 1999, 29, 718-726.
29. Allen, J. P., Litten, R. Z., Recommendations on use of biomarkers in alcoholism treatment trials. Alcohol. Clin. Exp. Res. 2003, 27, 1667-1670.
30. Klaiber, M. et al., A cardiac pathway of cyclic GMP-independent signaling of guanylyl cyclase A, the receptor for atrial natriuretic peptide. Proc. Natl. Acad. Sci. USA. 2011, 108, 18500-18505.
31. Elesgaray, R., Dankworth, B., Kruse, M., Hartmann, M. et al., Signaling cascade that mediates endothelial nitric oxide synthase activation induced by atrial natriuretic peptide. Regul. Pept. 2008, 151, 130-134.
32. Rolo, A. P., Palmeira, C. M., Diabetes and mitochondrial function: Role of hyperglycemia and oxidative stress. Toxicol. Appl. Pharmacol. 2006, 212, 167-178.
33. King, G. L., Loeken, M. R., Hyperglycemia-induced oxidative stress in diabetic complications. Histochem. Cell Biol. 2004, 122, 333-338.
34. Kawahito, S., Kitahata, H., Oshita, S., Problems associated with glucose toxicity: Role of hyperglycemia-induced oxidative stress. World J. Gastroenterol. 2009, 15, 4137-4142.
35. de Bono, B., Hoehndorf, R., Wimalaratne, S., Gkoutos, G., Grenon, P., The RICORDO approach to semantic interoperability for biomedical data and models: strategy, standards and solutions. BMC Res. Notes 2011, 4, 313.
36. Wimalaratne, S. M., Grenon, P., Hoehndorf, R., Gkoutos, G. V., de Bono, B., An infrastructure for ontology-based information systems in biomedicine: RICORDO case study. Bioinformatics 2012, 28, 448-450.
37. Ingenerf, J., Linder, R., Assessing applicability of ontological principles to different types of biomedical vocabularies. Methods Inf. Med. 2009, 48, 459-467.
38. Ashburner, M., Lewis, S., On ontologies for biologists: The Gene Ontology - untangling the web. Novartis Found. Symp. 2002, 247, 66-80; discussion 80-83, 84-90, 244-252.
39. de Matos, P., Alcántara, R., Dekker, A., Ennis, M. et al., Chemical entities of biological interest: An update. Nucleic Acids Res. 2010, 38, (Databaseissue) D249-54.
40. Natale, D. A., Arighi, C. N., Barker, W. C., Blake, J. A. et al., The Protein Ontology: A structured representation of protein forms and complexes. Nucleic Acids Res. 2011, 39, (Databaseissue) D539-545.
41. Rosse, C., Mejino, J. L. Jr., A reference ontology for biomedical informatics: The Foundational Model of Anatomy. J. Biomed. Inform. 2003, 36, 478-500.
42. de Bono, B., Sammut, S. J., Grenon, P., Achieving semantic interoperability between physiology models and clinical data. Proceedings of the 2011 Seventh IEEE International Conference on e-Science Workshops, 2011, 135-14.
43. Merrill, G. H., Concepts and synonymy in the UMLS Metathesaurus. J. Biomed. Discov. Collab. 2009, 4, 7.
44. Beard, D. A., Britten, R., Cooling, M. T., Garny, A. et al., CellML metadata: Standards, associated tools and repositories. Philos. Transact. A Math. Phys. Eng. Sci. 2009, 367, 1845-1867.
45. Cuellar, A. A., Lloyd, C. M., Nielsen, P. M. F., Bullivant, D. P. et al., An Overview of CellML 1.1, a Biological Model Description Language. Simul.-Trans. Soc. M. S. 2003, 79, 740-747.
46. de Bono, B., Grenon, P., Sammut, S. J., ApiNATOMY: A novel toolkit for visualizing multiscale anatomy schematics with phenotype-related information. Hum. Mutat. 2012, 33, 837-848.