Bioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, Georges-Köhler-Allee 106, Freiburg 79110, Germany.
Erasmus Medical Centre, Wytemaweg 80, Rotterdam 3015 CN, the Netherlands.
Cell Syst. 2018 Jun 27;6(6):752-758.e1. doi: 10.1016/j.cels.2018.05.012.
The primary problem with the explosion of biomedical datasets is not the data, not computational resources, and not the required storage space, but the general lack of trained and skilled researchers to manipulate and analyze these data. Eliminating this problem requires development of comprehensive educational resources. Here we present a community-driven framework that enables modern, interactive teaching of data analytics in life sciences and facilitates the development of training materials. The key feature of our system is that it is not a static but a continuously improved collection of tutorials. By coupling tutorials with a web-based analysis framework, biomedical researchers can learn by performing computation themselves through a web browser without the need to install software or search for example datasets. Our ultimate goal is to expand the breadth of training materials to include fundamental statistical and data science topics and to precipitate a complete re-engineering of undergraduate and graduate curricula in life sciences. This project is accessible at https://training.galaxyproject.org.
生物医学数据集爆炸带来的主要问题不是数据、计算资源，也不是所需的存储空间，而是缺乏训练有素的专业研究人员来操作和分析这些数据。要解决这个问题，需要开发全面的教育资源。在这里，我们提出了一个社区驱动的框架，使生命科学领域的数据分析能够实现现代化、互动式教学，并促进培训材料的开发。我们系统的关键特点是，它不是一个静态的教程集合，而是一个不断改进的集合。通过将教程与基于网络的分析框架相结合，生物医学研究人员可以通过网络浏览器自己进行计算，而无需安装软件或搜索示例数据集。我们的最终目标是扩展培训材料的广度，包括基本的统计和数据科学主题，并彻底改变生命科学领域的本科和研究生课程。该项目可在 https://training.galaxyproject.org 上访问。
