Technical University of Munich, Computational Mass Spectrometry, 85354 Freising, Bavaria, Germany.
Technical University of Munich, Chair of Proteomics and Bioanalytics, 85354 Freising, Bavaria, Germany.
Nucleic Acids Res. 2022 Jan 7;50(D1):D1541-D1552. doi: 10.1093/nar/gkab1026.
ProteomicsDB (https://www.ProteomicsDB.org) is a multi-omics and multi-organism resource for life science research. In this update, we present our efforts to continuously develop and expand ProteomicsDB. The major focus over the last two years was improving the findability, accessibility, interoperability and reusability (FAIR) of the data as well as its implementation. For this purpose, we release a new application programming interface (API) that provides systematic access to essentially all data in ProteomicsDB. Second, we release a new open-source user interface (UI) and show the advantages the scientific community gains from such software. With the new interface, two new visualizations of protein primary, secondary and tertiary structure as well an updated spectrum viewer were added. Furthermore, we integrated ProteomicsDB with our deep-neural-network Prosit that can predict the fragmentation characteristics and retention time of peptides. The result is an automatic processing pipeline that can be used to reevaluate database search engine results stored in ProteomicsDB. In addition, we extended the data content with experiments investigating different human biology as well as a newly supported organism.
ProteomicsDB(https://www.ProteomicsDB.org)是一个多组学和多生物体资源,用于生命科学研究。在本次更新中,我们介绍了我们不断开发和扩展 ProteomicsDB 的努力。过去两年的主要重点是提高数据的可发现性、可访问性、互操作性和可重用性(FAIR)及其实现。为此,我们发布了一个新的应用程序编程接口(API),该接口可系统地访问 ProteomicsDB 中的所有数据。其次,我们发布了一个新的开源用户界面(UI),并展示了科学界从这种软件中获得的优势。通过新的界面,添加了两种蛋白质一级、二级和三级结构的新可视化以及更新的光谱查看器。此外,我们将 ProteomicsDB 与我们的深度神经网络 Prosit 集成,该网络可以预测肽的片段特征和保留时间。其结果是一个自动处理管道,可用于重新评估存储在 ProteomicsDB 中的数据库搜索引擎结果。此外,我们扩展了数据内容,包括调查不同人类生物学的实验以及新支持的生物体。