Data mining with iPlant: a meeting report from the 2013 GARNet workshop, Data mining with iPlant.
Data mining with iPlant: a meeting report from the 2013 GARNet workshop, Data mining with iPlant.
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DOI：
10.1093/jxb/eru402
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发表时间：
2015
影响因子：
6.9
通讯作者：
Lisa Martin;Charis Cook;Naim Matasci;Jason J. Williams;R. Bastow
中科院分区：
文献类型：
--
作者：
Lisa Martin;Charis Cook;Naim Matasci;Jason J. Williams;R. Bastow
高通量测序技术已迅速从大型国际测序中心转移到单个实验室。这些变化推动了现代生物学的“数据洪流”。例如，自1982年以来，向GenBank提交的核苷酸序列的大小每年都翻了一番，单个数据集的大小现在经常达到TB级。虽然大数据为科学发现提供了令人兴奋的机会，但数据分析技能并不是典型的湿凳生物学家经验的一部分。知道如何处理数据、如何可视化和分析数据、做出预测和检验假设是成功的重要障碍。许多研究人员也缺乏足够的能力来存储和共享这些数据，这进一步阻碍了小组和研究所之间的有效合作。美国国家科学基金会资助的iFactory Collaborative成立于2008年，旨在形成数据收集和分析管道的一部分，并帮助缓解与植物科学中的大数据挑战相关的瓶颈。IFactory利用高性能计算设施的强大功能，提供免费使用的网络基础设施，以实现TB级的数据存储、改进分析和促进协作。为了帮助培训英国植物科学研究人员使用iPLANT平台，并了解如何利用它进行进一步研究，Garnet于2013年9月在华威大学与iPLANT组织了为期四天的数据挖掘研讨会。这份报告概述了研讨会的情况，并强调了iFactory环境在降低使用复杂生物信息学资源的障碍、促进植物科学研究的发现以及为教育和推广计划提供平台方面的力量。
High-throughput sequencing technologies have rapidly moved from large international sequencing centres to individual laboratory benchtops. These changes have driven the 'data deluge' of modern biology. Submissions of nucleotide sequences to GenBank, for example, have doubled in size every year since 1982, and individual data sets now frequently reach terabytes in size. While 'big data' present exciting opportunities for scientific discovery, data analysis skills are not part of the typical wet bench biologist's experience. Knowing what to do with data, how to visualize and analyse them, make predictions, and test hypotheses are important barriers to success. Many researchers also lack adequate capacity to store and share these data, creating further bottlenecks to effective collaboration between groups and institutes. The US National Science Foundation-funded iPlant Collaborative was established in 2008 to form part of the data collection and analysis pipeline and help alleviate the bottlenecks associated with the big data challenge in plant science. Leveraging the power of high-performance computing facilities, iPlant provides free-to-use cyberinfrastructure to enable terabytes of data storage, improve analysis, and facilitate collaborations. To help train UK plant science researchers to use the iPlant platform and understand how it can be exploited to further research, GARNet organized a four-day Data mining with iPlant workshop at Warwick University in September 2013. This report provides an overview of the workshop, and highlights the power of the iPlant environment for lowering barriers to using complex bioinformatics resources, furthering discoveries in plant science research and providing a platform for education and outreach programmes.