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SIGNOR 2.0,即信号网络开放资源 2.0:2019 年更新。

SIGNOR 2.0, the SIGnaling Network Open Resource 2.0: 2019 update.

机构信息

Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133 Rome, Italy.

European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK.

出版信息

Nucleic Acids Res. 2020 Jan 8;48(D1):D504-D510. doi: 10.1093/nar/gkz949.

Abstract

The SIGnaling Network Open Resource 2.0 (SIGNOR 2.0) is a public repository that stores signaling information as binary causal relationships between biological entities. The captured information is represented graphically as a signed directed graph. Each signaling relationship is associated to an effect (up/down-regulation) and to the mechanism (e.g. binding, phosphorylation, transcriptional activation, etc.) causing the up/down-regulation of the target entity. Since its first release, SIGNOR has undergone a significant content increase and the number of annotated causal interactions have almost doubled. SIGNOR 2.0 now stores almost 23 000 manually-annotated causal relationships between proteins and other biologically relevant entities: chemicals, phenotypes, complexes, etc. We describe here significant changes in curation policy and a new confidence score, which is assigned to each interaction. We have also improved the compliance to the FAIR data principles by providing (i) SIGNOR stable identifiers, (ii) programmatic access through REST APIs, (iii) bioschemas and (iv) downloadable data in standard-compliant formats, such as PSI-MI CausalTAB and GMT. The data are freely accessible and downloadable at https://signor.uniroma2.it/.

摘要

SIGnaling Network Open Resource 2.0(SIGNOR 2.0)是一个公共存储库,它将信号信息存储为生物实体之间的二进制因果关系。捕获的信息以有向图的形式表示为有符号的。每个信号关系都与一个效应(上调/下调)和导致目标实体上调/下调的机制(例如结合、磷酸化、转录激活等)相关联。自首次发布以来,SIGNOR 的内容有了显著的增加,注释的因果相互作用数量几乎翻了一番。SIGNOR 2.0 现在存储了近 23000 个手动注释的蛋白质和其他生物相关实体(化学物质、表型、复合物等)之间的因果关系。我们在这里描述了策展政策的重大变化和新的置信度评分,该评分分配给每个交互作用。我们还通过提供(i)SIGNOR 稳定标识符、(ii)通过 REST API 进行编程访问、(iii)bioschemas 和(iv)符合标准的可下载数据(如 PSI-MI CausalTAB 和 GMT),提高了对 FAIR 数据原则的遵守程度。数据可在 https://signor.uniroma2.it/ 免费访问和下载。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5211/7145695/41eddd670c8f/gkz949fig1.jpg

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