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免疫球蛋白:通过手动编辑的细胞间免疫相互作用网络实现系统免疫学。

ImmunoGlobe: enabling systems immunology with a manually curated intercellular immune interaction network.

机构信息

Canary Center at Stanford, Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA.

Stanford University, Stanford, CA, USA.

出版信息

BMC Bioinformatics. 2020 Aug 10;21(1):346. doi: 10.1186/s12859-020-03702-3.

Abstract

BACKGROUND

While technological advances have made it possible to profile the immune system at high resolution, translating high-throughput data into knowledge of immune mechanisms has been challenged by the complexity of the interactions underlying immune processes. Tools to explore the immune network are critical for better understanding the multi-layered processes that underlie immune function and dysfunction, but require a standardized network map of immune interactions. To facilitate this we have developed ImmunoGlobe, a manually curated intercellular immune interaction network extracted from Janeway's Immunobiology textbook.

RESULTS

ImmunoGlobe is the first graphical representation of the immune interactome, and is comprised of 253 immune system components and 1112 unique immune interactions with detailed functional and characteristic annotations. Analysis of this network shows that it recapitulates known features of the human immune system and can be used uncover novel multi-step immune pathways, examine species-specific differences in immune processes, and predict the response of immune cells to stimuli. ImmunoGlobe is publicly available through a user-friendly interface at www.immunoglobe.org and can be downloaded as a computable graph and network table.

CONCLUSION

While the fields of proteomics and genomics have long benefited from network analysis tools, no such tool yet exists for immunology. ImmunoGlobe provides a ground truth immune interaction network upon which such tools can be built. These tools will allow us to predict the outcome of complex immune interactions, providing mechanistic insight that allows us to precisely modulate immune responses in health and disease.

摘要

背景

虽然技术进步已经使得以高分辨率描绘免疫系统成为可能,但将高通量数据转化为对免疫机制的了解,一直受到免疫过程中潜在相互作用复杂性的挑战。探索免疫网络的工具对于更好地理解免疫功能和功能障碍的多层次过程至关重要,但需要一个标准化的免疫相互作用网络图谱。为了促进这一点,我们开发了 ImmunoGlobe,这是从 Janeway 的《免疫生物学》教科书中提取的人工策免疫系统细胞间相互作用网络。

结果

ImmunoGlobe 是免疫相互作用组的第一个图形表示,它由 253 个免疫系统成分和 1112 个独特的免疫相互作用组成,具有详细的功能和特征注释。对该网络的分析表明,它再现了人类免疫系统的已知特征,可以用于发现新的多步骤免疫途径,检查免疫过程中的物种特异性差异,并预测免疫细胞对刺激的反应。ImmunoGlobe 通过 www.immunoglobe.org 的用户友好界面公开提供,并且可以作为可计算的图和网络图下载。

结论

尽管蛋白质组学和基因组学领域长期以来一直受益于网络分析工具,但免疫学领域还没有这样的工具。ImmunoGlobe 提供了一个免疫相互作用的真实网络,这些工具可以在此基础上构建。这些工具将使我们能够预测复杂免疫相互作用的结果,提供机制上的洞察力,使我们能够在健康和疾病中精确调节免疫反应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ad1/7430879/f1fc9ee7976e/12859_2020_3702_Fig1_HTML.jpg

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