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研究技巧简述:全基因组生物学的生物信息学。

Research Techniques Made Simple: Bioinformatics for Genome-Scale Biology.

机构信息

The Dermatology Centre, Salford Royal NHS Foundation Trust, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.

William Harvey Research Institute, Centre for Translational Bioinformatics, Barts and The London School of Medicine and Dentistry, Charterhouse Square, London, UK.

出版信息

J Invest Dermatol. 2017 Sep;137(9):e163-e168. doi: 10.1016/j.jid.2017.07.095.

Abstract

High-throughput biology presents unique opportunities and challenges for dermatological research. Drawing on a small handful of exemplary studies, we review some of the major lessons of these new technologies. We caution against several common errors and introduce helpful statistical concepts that may be unfamiliar to researchers without experience in bioinformatics. We recommend specific software tools that can aid dermatologists at varying levels of computational literacy, including platforms with command line and graphical user interfaces. The future of dermatology lies in integrative research, in which clinicians, laboratory scientists, and data analysts come together to plan, execute, and publish their work in open forums that promote critical discussion and reproducibility. In this article, we offer guidelines that we hope will steer researchers toward best practices for this new and dynamic era of data intensive dermatology.

摘要

高通量生物学为皮肤科研究带来了独特的机遇和挑战。本文以少数几个典型研究为例,综述了这些新技术的一些主要经验教训。我们提醒大家注意一些常见错误,并介绍了一些对没有生物信息学经验的研究人员来说可能不熟悉的有用统计概念。我们推荐了一些特定的软件工具,这些工具可以帮助不同计算水平的皮肤科医生,包括带有命令行和图形用户界面的平台。皮肤科的未来在于整合研究,即临床医生、实验室科学家和数据分析人员聚集在一起,在开放论坛中规划、执行和发表他们的工作,以促进批判性讨论和可重复性。在本文中,我们提供了一些指导方针,希望能引导研究人员采用最佳实践,以适应这个新的、充满活力的数据密集型皮肤科时代。

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