jPOSTrepo: an international standard data repository for proteomes

By Shujiro Okuda, Yu Watanabe, Yuki Moriya, S. Kawano, Tadashi Yamamoto, M. Matsumoto, Tomoyo Takami, Daiki Kobayashi, N. Araki, A. C. Yoshizawa and 4 more. 2016

604 citations recorded by the source corpus.

Major advancements have recently been made in mass spectrometry-based proteomics, yielding an increasing number of datasets from various proteomics projects worldwide. In order to facilitate the sharing and reuse of promising datasets, it is important to construct appropriate, high-quality public data repositories. jPOSTrepo (https://repository.jpostdb.org/) has successfully implemented several unique features, including high-speed file uploading, flexible file management and easy-to-use interfaces. This repository has been launched as a public repository containing various proteomic datasets and is available for researchers worldwide. In addition, our repository has joined the ProteomeXchange consortium, which includes the most popular public repositories such as PRIDE in Europe for MS/MS datasets and PASSEL for SRM datasets in the USA. Later MassIVE was introduced in the USA and accepted into the ProteomeXchange, as was our repository in July 2016, providing important datasets from Asia/Oceania. Accordingly, this repository thus contributes to a global alliance to share and store all datasets from a wide variety of proteomics experiments. Thus, the repository is expected to become a major repository, particularly for data collected in the Asia/Oceania region.

Subfields: Molecular Biology, Spectroscopy

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Citations in the corpus

The ProteomeXchange consortium at 10 years: 2023 update (2022, background): “Four additional resources have joined PX over the years, which are listed next in chronological order: MassIVE (University of California San Diego, USA, in 2014), jPOST (8) (the jPOST project, Japan, in 2016), iProX (9) (National Center for Protein Sciences, Beijing, China, in 2017), and Panorama Pu”
The PRIDE database and related tools and resources in 2019: improving support for quantification data (2018, neutral): “edu/), jPOSTrepo (6), iProx (http://www.”