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3
Advancing personalized health care through health information technology: an update from the American Health Information Community's Personalized Health Care Workgroup.通过健康信息技术推进个性化医疗保健:美国健康信息社区个性化医疗保健工作组的最新情况
J Am Med Inform Assoc. 2008 Jul-Aug;15(4):391-6. doi: 10.1197/jamia.M2718. Epub 2008 Apr 24.
4
Mechanisms and dynamics of protein clustering on a solid surface.蛋白质在固体表面聚集的机制与动力学
Phys Rev Lett. 2008 Feb 15;100(6):068102. doi: 10.1103/PhysRevLett.100.068102. Epub 2008 Feb 12.
5
Critical issues in bioinformatics and computing.生物信息学与计算中的关键问题。
Perspect Health Inf Manag. 2004 Oct 11;1:9.
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Integrated analysis of gene expression by Association Rules Discovery.通过关联规则发现进行基因表达的综合分析。
BMC Bioinformatics. 2006 Feb 7;7:54. doi: 10.1186/1471-2105-7-54.
7
Minimum redundancy feature selection from microarray gene expression data.从微阵列基因表达数据中进行最小冗余特征选择。
J Bioinform Comput Biol. 2005 Apr;3(2):185-205. doi: 10.1142/s0219720005001004.
8
A survey of current work in biomedical text mining.生物医学文本挖掘的当前工作调查。
Brief Bioinform. 2005 Mar;6(1):57-71. doi: 10.1093/bib/6.1.57.
9
Synergy between medical informatics and bioinformatics: facilitating genomic medicine for future health care.医学信息学与生物信息学之间的协同作用:推动基因组医学服务未来医疗保健。
J Biomed Inform. 2004 Feb;37(1):30-42. doi: 10.1016/j.jbi.2003.09.003.
10
Functional classification of proteins for the prediction of cellular function from a protein-protein interaction network.基于蛋白质-蛋白质相互作用网络预测细胞功能的蛋白质功能分类
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转化生物信息学与医疗保健信息学:计算与伦理挑战。

Translational bioinformatics and healthcare informatics: computational and ethical challenges.

作者信息

Sethi Prerna, Theodos Kimberly

机构信息

Department of Health Information Management, Louisiana Tech University, Ruston, LA, USA.

出版信息

Perspect Health Inf Manag. 2009 Sep 16;6(Fall):1h.

PMID:20169020
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2804463/
Abstract

Exponentially growing biological and bioinformatics data sets present a challenge and an opportunity for researchers to contribute to the understanding of the genetic basis of phenotypes. Due to breakthroughs in microarray technology, it is possible to simultaneously monitor the expressions of thousands of genes, and it is imperative that researchers have access to the clinical data to understand the genetics and proteomics of the diseased tissue. This technology could be a landmark in personalized medicine, which will provide storage for clinical and genetic data in electronic health records (EHRs). In this paper, we explore the computational and ethical challenges that emanate from the intersection of bioinformatics and healthcare informatics research. We describe the current situation of the EHR and its capabilities to store clinical and genetic data and then discuss the Genetic Information Nondiscrimination Act. Finally, we posit that the synergy obtained from the collaborative efforts between the genomics, clinical, and healthcare disciplines has potential to enhance and promote faster and more advanced breakthroughs in healthcare.

摘要

呈指数级增长的生物学和生物信息学数据集,对研究人员理解表型的遗传基础而言,既是挑战也是机遇。由于微阵列技术的突破,能够同时监测数千个基因的表达,研究人员必须获取临床数据,以了解患病组织的遗传学和蛋白质组学。这项技术可能成为个性化医疗的一个里程碑,它将在电子健康记录(EHR)中存储临床和遗传数据。在本文中,我们探讨了生物信息学与医疗信息学研究交叉产生的计算和伦理挑战。我们描述了EHR的现状及其存储临床和遗传数据的能力,然后讨论了《遗传信息非歧视法案》。最后,我们认为,基因组学、临床和医疗保健学科之间的协同合作,有潜力在医疗保健领域推动更快、更先进的突破。