collectNET: a web server for integrated inference of cell-cell communication network.

IF 3.4 4区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY Database: The Journal of Biological Databases and Curation Pub Date : 2024-09-16 DOI:10.1093/database/baae098
Yan Pan, Zijing Gao, Xuejian Cui, Zhen Li, Rui Jiang
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Abstract

Cell-cell communication (CCC) through ligand-receptor (L-R) pairs forms the cornerstone for complex functionalities in multicellular organisms. Deciphering such intercellular signaling can contribute to unraveling disease mechanisms and enable targeted therapy. Nonetheless, notable biases and inconsistencies are evident among the inferential outcomes generated by current methods for inferring CCC network. To fill this gap, we developed collectNET (http://health.tsinghua.edu.cn/collectnet) as a comprehensive web platform for analyzing CCC network, with efficient calculation, hierarchical browsing, comprehensive statistics, advanced searching, and intuitive visualization. collectNET provides a reliable online inference service with prior knowledge of three public L-R databases and systematic integration of three mainstream inference methods. Additionally, collectNET has assembled a human CCC atlas, including 126 785 significant communication pairs based on 343 023 cells. We anticipate that collectNET will benefit researchers in gaining a more holistic understanding of cell development and differentiation mechanisms. Database URL: http://health.tsinghua.edu.cn/collectnet.

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collectNET:用于小区通信网络综合推理的网络服务器。
通过配体-受体(L-R)对进行的细胞-细胞通讯(CCC)是多细胞生物体复杂功能的基石。破译这种细胞间信号转导有助于揭示疾病机理,实现靶向治疗。然而,目前推断 CCC 网络的方法所产生的推断结果存在明显的偏差和不一致。为了填补这一空白,我们开发了 collectNET (http://health.tsinghua.edu.cn/collectnet),作为分析 CCC 网络的综合网络平台,它具有高效计算、分层浏览、全面统计、高级搜索和直观可视化等特点。collectNET 预先了解三个公共 L-R 数据库,并系统整合了三种主流推断方法,从而提供了可靠的在线推断服务。此外,collectNET 还绘制了人类 CCC 图集,其中包括基于 343 023 个细胞的 126 785 个重要通讯对。我们预计,collectNET 将有助于研究人员更全面地了解细胞发育和分化机制。数据库网址:http://health.tsinghua.edu.cn/collectnet。
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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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