基于表型组和蛋白质关联的人类疾病基因预测

Guangri Quan, Yu Du, Junheng Huang, Yadong Wang
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引用次数: 1

摘要

疾病基因鉴定是人类遗传病治疗问题的关键。本文介绍了一种基于临床表现与蛋白-蛋白相互作用网络关系的人类遗传病基因预测新方法。提出了一种基于关联概率和Pearson相关系数的预测模型。这个数学模型反映了表型相似性和蛋白质相互作用之间关联的规律性。它比传统模型更能描述真实的生物系统,具有更强的预测能力。
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Prediction of Human Disease Genes Based on Associations between Phenome and Proteins
Disease genes identification is the key to the issue of human genetic diseases cure. This paper describes a new method of human genetic disease gene prediction, which is based on the relations between clinical manifestations and protein-protein interaction network. A new prediction model which is based on associated probability and Pearson correlation coefficient is also described. This mathematical model reflects the regularity of associations between similarities of phenotypes and interactions of proteins. It can discribe the real biological systems better than traditional models, and gives a stronger predictive ability.
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