遇见数据集

CovMulNet19.zip

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Figshare2020-11-20 更新2026-04-08 收录
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CovMulNet19 is a comprehensive network containing all available known interactions involving SARS-CoV-2 proteins, interacting-human proteins, diseases and symptoms that are related to these human proteins, and compounds that can potentially target them. Extensive network analysis methods, based on a bootstrap approach, allow us to prioritise a list of diseases that display a high similarity to \covid and a list of drugs that could potentially be beneficial to treat patients. As a key feature of CovMulNet19, the inclusion of symptoms allows a deeper characterization of the disease pathology, representing a useful proxy for CoVid19-related molecular processes. We recapitulate many of the known symptoms of the disease and we find the most similar diseases to COVID-19 reflect conditions that are risk factors in patients. <br>

CovMulNet19是一个综合性互作网络,涵盖了目前已报道的所有与严重急性呼吸综合征冠状病毒2(SARS-CoV-2)蛋白、与之发生相互作用的人类蛋白、与这些人类蛋白相关的疾病及症状,以及可潜在靶向上述靶点的化合物。本数据集基于Bootstrap方法(bootstrap approach)构建了全面的网络分析流程,可优先筛选得到与新型冠状病毒肺炎(COVID-19)高度相似的疾病候选列表,以及潜在可用于临床治疗患者的药物候选列表。作为CovMulNet19的核心特色,纳入症状信息可实现对疾病病理的更深入刻画,可作为新冠病毒感染相关分子过程的有效替代表征指标。本数据集复现了该疾病的诸多已知典型症状,且筛选得到的与COVID-19最相似的疾病均为患者群体中的高危风险相关病症。

提供机构:
Arsham Ghavasieh
创建时间:
2020-11-20
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