Ten Simples Rules on How to Organise a Bioinformatics Hackathon

Susanne Hollmann, B. Regierer, T. Attwood, A. Gisel, J. van Helden, G. Rossier, P. Kersey, E. Korpelainen, G. Vriend, E. Bongcam-Rudloff
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Abstract

The completion of the human genome sequence triggered worldwide efforts to unravel the secrets hidden in its deceptively simple code. Numerous bioinformatics projects were undertaken to hunt for genes, predict their protein products, function and post-translational modifications, analyse protein-protein interactions, etc. Many novel analytic and predictive computer programmes fully optimised for manipulating human genome sequence data have been developed, whereas considerably less effort has been invested in exploring the many thousands of other available genomes, from unicellular organisms to plants and non-human animals.  Nevertheless, a detailed understanding of these organisms can have a significant impact on human health and well-being.New advances in genome sequencing technologies, bioinformatics, automation, artificial intelligence, etc., enable us to extend the reach of genomic research to all organisms.  To this aim gather, develop and implement new bioinformatics solutions (usually in the form of software) is pivotal. A helpful model, often used by the bioinformatics community, is the so-called hackathon. These are events when all stakeholders beyond their disciplines work together creatively to solve a problem. During its runtime, the consortium of the EU-funded project AllBio - Broadening the Bioinformatics Infrastructure to cellular, animal and plant science - conducted many successful hackathons with researchers from different Life Science areas. Based on this experience, in the following, the authors present a step-by-step and standardised workflow explaining how to organise a bioinformatics hackathon to develop software solutions to biological problems.
关于如何组织生物信息学黑客马拉松的十条简单规则
人类基因组序列的完成引发了全世界的努力,以揭开隐藏在其看似简单的代码中的秘密。许多生物信息学项目被用于寻找基因,预测它们的蛋白质产物、功能和翻译后修饰,分析蛋白质之间的相互作用等。许多新的分析和预测计算机程序已经开发出来,充分优化了对人类基因组序列数据的操作,而在探索从单细胞生物到植物和非人类动物的数千种其他可用基因组方面投入的努力要少得多。然而,对这些生物的详细了解可以对人类健康和福祉产生重大影响。基因组测序技术、生物信息学、自动化、人工智能等方面的新进展,使我们能够将基因组研究的范围扩展到所有生物体。为了实现这一目标,收集、开发和实施新的生物信息学解决方案(通常以软件的形式)是关键。生物信息学社区经常使用的一个有用的模式是所谓的黑客马拉松。这些事件是所有的利益相关者超越他们的学科创造性地一起工作来解决问题。在运行期间,欧盟资助的AllBio项目——将生物信息学基础设施扩展到细胞、动物和植物科学——与来自不同生命科学领域的研究人员成功地举办了许多黑客马拉松。基于这一经验,在下文中,作者介绍了一个逐步和标准化的工作流程,解释如何组织生物信息学黑客马拉松来开发生物问题的软件解决方案。
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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