Enabling pharmacogenomic services: Informatics and computational discovery aspects

G. Potamias, Kleanthi Lakiotaki, Evgenia Kartsaki, A. Kanterakis, T. Katsila, G. Patrinos
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Abstract

We present ePGA (electronic Pharmacogenomics Assistant), a web-based system that offers two main services to the engaged pharmacogenomic biomedical communities namely, explore - a service to search and browse through established pharmacogenomic gene-drug associations, and translate - a service to infer metabolizing phenotypes from individual genotype profiles. Furthermore, we present our work on utilizing a machine-learning methodology (decision-tree induction) in order to induce generalized pharmacogenomic translation models from known haplotype-tables that are able to infer the metabolizer status of individuals from their genotype profiles. Preliminary results are highly predictive, and highlight the potential of the whole approach. The whole work falls into the rising field of Pharmacogenomic Informatics.
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使药物基因组学服务:信息学和计算发现方面
我们提出了ePGA(电子药物基因组学助理),一个基于网络的系统,为参与药物基因组学生物医学社区提供两项主要服务,即探索-一项搜索和浏览已建立的药物基因组学基因-药物关联的服务,以及翻译-一项从个体基因型谱推断代谢表型的服务。此外,我们介绍了我们利用机器学习方法(决策树归纳)的工作,以便从已知的单倍型表中归纳出广义的药物基因组学翻译模型,该模型能够从个体的基因型谱中推断出个体的代谢状态。初步结果具有很高的预测性,并突出了整个方法的潜力。整个工作属于新兴的药物基因组信息学领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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