CovMulNet19.zip

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是一款综合性网络数据集，涵盖了目前公开的所有与严重急性呼吸综合征冠状病毒2（SARS-CoV-2）相关的已知相互作用，具体包括SARS-CoV-2蛋白与人类蛋白的相互作用、与这些人类蛋白相关的疾病及症状，以及可对上述靶点产生靶向作用的潜在化合物。依托自举法（bootstrap）的多维度网络分析方法，本团队得以对两类对象进行优先排序：一是与新型冠状病毒肺炎（COVID-19）高度相似的疾病列表，二是有望用于临床治疗的候选药物列表。作为CovMulNet19的核心特征之一，纳入症状信息可实现对该疾病病理的更深入表征，可作为新冠病毒感染相关分子进程的有效替代指标。本数据集复现了该疾病诸多已知临床症状，且筛选得到的与COVID-19最相似的疾病，均为新冠患者的已知风险相关病症。