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Critical role of bioinformatics in translating huge amounts of next-generation sequencing data into personalized medicine

机译:生物信息学在将大量下一代测序数据转化为个性化医学中的关键作用

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Realizing personalized medicine requires integrating diverse data types with bioinformatics. The most vital data are genomic information for individuals that are from advanced next-generation sequencing (NGS) technologies at present. The technologies continue to advance in terms of both decreasing cost and sequencing speed with concomitant increase in the amount and complexity of the data. The prodigious data together with the requisite computational pipelines for data analysis and interpretation are stressors to IT infrastructure and the scientists conducting the work alike. Bioinformatics is increasingly becoming the rate-limiting step with numerous challenges to be overcome for translating NGS data for personalized medicine. We review some key bioinformatics tasks, issues, and challenges in contexts of IT requirements, data quality, analysis tools and pipelines, and validation of biomarkers.
机译:实现个性化医学需要将多种数据类型与生物信息学整合在一起。目前最重要的数据是来自先进的下一代测序(NGS)技术的个人基因组信息。在降低成本和排序速度方面,技术不断进步,同时,数据的数量和复杂性也随之增加。庞大的数据以及用于数据分析和解释的必要计算管道,成为IT基础架构和进行此项工作的科学家的压力所在。生物信息学正日益成为限制速率的步骤,在翻译个性化医学的NGS数据时要克服许多挑战。我们在IT需求,数据质量,分析工具和管道以及生物标记物验证的背景下,审查了一些关键的生物信息学任务,问题和挑战。

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