SEPDB:分泌蛋白数据库。

IF 3.4 4区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Ruiqing Wang, Chao Ren, Tian Gao, Hao Li, Xiaochen Bo, Dahai Zhu, Dan Zhang, Hebing Chen, Yong Zhang
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引用次数: 0

摘要

检测血清中分泌蛋白的动态变化一直是蛋白质组学面临的挑战。分泌蛋白数据库(SEPDB)是一个综合性分泌蛋白组学数据库,提供从血清、外泌体和细胞培养基中收集的人类、小鼠和大鼠分泌蛋白组学数据集。SEPDB 编译来自分泌蛋白数据库、UniProt 和人类蛋白质图谱数据库的分泌蛋白信息,根据蛋白质亚细胞定位和疾病标志物对分泌蛋白组学数据进行注释。SEPDB 整合了最新的预测建模技术来测量分泌蛋白信号肽结构分布的偏差,通过排除跨膜结构域蛋白来扩展信号肽序列预测,并更新了分泌蛋白的验证分析管道。为了建立组织特异性档案,我们还创建了与不同人体组织相关的分泌蛋白组学数据集。此外,我们还提供了有关异质性受体网络组织关系的信息,反映了作为配体的分泌蛋白分子结构中固有的复杂功能信息。用户可以利用 SEPDB 的刷新搜索、分析、浏览和下载功能,该数据库的在线网址为 https://sysomics.com/SEPDB/。数据库网址:https://sysomics.com/SEPDB/。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SEPDB: a database of secreted proteins.

Detecting changes in the dynamics of secreted proteins in serum has been a challenge for proteomics. Enter secreted protein database (SEPDB), an integrated secretory proteomics database offering human, mouse and rat secretory proteomics datasets collected from serum, exosomes and cell culture media. SEPDB compiles secreted protein information from secreted protein database, UniProt and Human Protein Atlas databases to annotate secreted proteomics data based on protein subcellular localization and disease markers. SEPDB integrates the latest predictive modeling techniques to measure deviations in the distribution of signal peptide structures of secreted proteins, extends signal peptide sequence prediction by excluding transmembrane structural domain proteins and updates the validation analysis pipeline for secreted proteins. To establish tissue-specific profiles, we have also created secreted proteomics datasets associated with different human tissues. In addition, we provide information on heterogeneous receptor network organizational relationships, reflective of the complex functional information inherent in the molecular structures of secreted proteins that serve as ligands. Users can take advantage of the Refreshed Search, Analyze, Browse and Download functions of SEPDB, which is available online at https://sysomics.com/SEPDB/. Database URL:  https://sysomics.com/SEPDB/.

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来源期刊
Database: The Journal of Biological Databases and Curation
Database: The Journal of Biological Databases and Curation MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
9.00
自引率
3.40%
发文量
100
审稿时长
>12 weeks
期刊介绍: Huge volumes of primary data are archived in numerous open-access databases, and with new generation technologies becoming more common in laboratories, large datasets will become even more prevalent. The archiving, curation, analysis and interpretation of all of these data are a challenge. Database development and biocuration are at the forefront of the endeavor to make sense of this mounting deluge of data. Database: The Journal of Biological Databases and Curation provides an open access platform for the presentation of novel ideas in database research and biocuration, and aims to help strengthen the bridge between database developers, curators, and users.
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