遇见数据集

Viral Host Range database

收藏
知名数据库2026-06-02 收录
官方服务:

资源简介:

The Viral Host Range database (VHRdb) represents a unique resource for the community to rapidly find, document analyze and disseminate data related to the range of hosts that a virus can infect. Over the years, countless host range experiments have been performed in many laboratories. However, these data are not readily available to the community and are therefore underexploited. The VHRdb is an online resource that centralizes experimental data related to the host range of viruses. While it originates from bacteriophages and bacteria interaction studies, its design is compatible with viruses infecting all living forms. Users can browse publicly available data to find which host is infected by a virus, and vice versa. Users can also upload their own data, with the option to keep it private or make it public, analyze results across independent sets of data, generate and visualize outputs. Data implemented in the VHRdb are linked to users and, if available, to publications and sequence identifiers. The VHRdb is an initiative from the Debarbieux lab and is developed and maintained in collaboration with the Bioinformatics and Biostatistics Hub of Institut Pasteur. If you wish to import a collection or very sizable data into the VHRdb, please do no hesitate to contact us to arrange details such as specific identifiers (see Documentation).

病毒宿主范围数据库(Viral Host Range database,简称VHRdb)是一款面向科研社群的独特资源,可帮助用户快速检索、记录、分析并传播与病毒可感染宿主范围相关的数据。多年来,全球诸多实验室已开展了大量宿主范围相关实验,但这些数据并未对科研社群开放共享,因此其应用价值未得到充分挖掘。VHRdb是一款在线资源,可集中整合与病毒宿主范围相关的实验数据。尽管该数据库最初源于噬菌体与细菌的相互作用研究,但其架构设计兼容所有感染活体细胞的病毒。用户可浏览公开数据集,查询某一病毒可感染的宿主,反之亦可查询某一宿主可被哪些病毒感染。用户亦可上传自有数据,并可选择将数据设为私有或公开;平台支持跨独立数据集开展结果分析,并可生成并可视化分析结果。录入VHRdb的数据均与上传用户关联,若有对应信息,还会关联至相关文献及序列标识符。VHRdb由Debarbieux实验室发起研发,并联合巴斯德研究所生物信息与生物统计学中心开发维护。若您希望向VHRdb导入批量数据集或超大规模数据,请随时联系我们以协商具体事宜,例如特定标识符相关细节(详见文档)。

提供机构:
巴斯德研究所
搜集汇总
数据集介绍
Viral Host Range database 数据集图片
背景与挑战
背景概述
Viral Host Range database(VHRdb)是一个专注于病毒与宿主相互作用研究的在线资源,它整合了实验数据以支持用户搜索病毒宿主范围或反向查询。该数据库允许用户贡献、分析和共享数据,旨在避免科学界重复进行相同测试,并提供了工具来比较不同数据集。
以上内容由遇见数据集搜集并总结生成
二维码
社区交流群
二维码
科研交流群
商业服务