Author(s)

Shao-Min Yan, Guang Wu

Computational Mutation Project, DreamSciTech Consulting, 301, Building 12, Nanyou A-zone, Jiannan Road, Shenzhen, Guangdong Province CN-518054, China;.
National Engineering Research Center for Non-food Biorefinery, Guangxi Academy of Sciences, 98 Daling Road, Nanning, Guangxi Province, CN-530007, China;.

In this study, we use the cross-impact analysis to build a descriptively probabilistic relationship between mutant von Hippel-Lindau protein and its clinical outcome after quantifying mutant von Hippel-Lindau proteins with the amino-acid distribution probability, then we use the Bayes-ian equation to determine the probability that the von Hippel-Lindau disease occurs under a mutation, and finally we attempt to distinguish the classifications of clinical outcomes as well as the endocrine and nonendocrine neoplasia induced by mutations of von Hippel-Lindau protein. The results show that a patient has 9/10 chance of being von Hippel-Lindau disease when a new mutation occurs in von Hippel- Lindau protein, the possible distinguishing of classifications of clinical outcomes using mod-eling, and the explanation of the endocrine and nonendocrine neoplasia in modeling view.

Amino Acid; Bayes’ Law; Cross-Impact Analysis; Distribution Probability; Mutation; Von Hip-pel-Lindau Disease

Yan, S. and Wu, G. (2009) Descriptively probabilistic relationship between mutated primary structure of von Hippel-Lindau protein and its clinical outcome. Journal of Biomedical Science and Engineering, 2, 190-199. doi: 10.4236/jbise.2009.23032.