Bekker Gert-Jan, Kawabata Takeshi, Kurisu Genji
Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Biophys Rev. 2020 Apr;12(2):371-375. doi: 10.1007/s12551-020-00632-5. Epub 2020 Feb 5.
We present the Biological Structure Model Archive (BSM-Arc, https://bsma.pdbj.org), which aims to collect raw data obtained via in silico methods related to structural biology, such as computationally modeled 3D structures and molecular dynamics trajectories. Since BSM-Arc does not enforce a specific data format for the raw data, depositors are free to upload their data without any prior conversion. Besides uploading raw data, BSM-Arc enables depositors to annotate their data with additional explanations and figures. Furthermore, via our WebGL-based molecular viewer Molmil, it is possible to recreate 3D scenes as shown in the corresponding scientific article in an interactive manner. To submit a new entry, depositors require an ORCID ID to login, and to finally publish the data, an accompanying peer-reviewed paper describing the work must be associated with the entry. Submitting their data enables researchers to not only have an external backup but also provide an opportunity to promote their work via an interactive platform and to provide third-party researchers access to their raw data.
我们展示了生物结构模型存档库(BSM-Arc,https://bsma.pdbj.org),其旨在收集通过与结构生物学相关的计算机模拟方法获得的原始数据,例如计算建模的3D结构和分子动力学轨迹。由于BSM-Arc不对原始数据强制使用特定的数据格式,因此存入者可以自由上传其数据而无需事先进行任何转换。除了上传原始数据外,BSM-Arc还使存入者能够用额外的解释和图表对其数据进行注释。此外,通过我们基于WebGL的分子查看器Molmil,可以以交互方式重现相应科学文章中所示的3D场景。要提交新条目,存入者需要一个ORCID ID进行登录,并且要最终发布数据,必须有一篇描述该工作的同行评审论文与该条目相关联。提交数据使研究人员不仅能够进行外部备份,还能通过一个交互式平台来推广他们的工作,并为第三方研究人员提供访问其原始数据的机会。