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| BII-Design: Exploring the ecology and evolution of the global virome with big data and machine learning | |
| 项目编号 | 2021909 |
| Colin Carlson | |
| 项目主持机构 | Georgetown University |
| 开始日期 | 2021-01-01 |
| 结束日期 | 12/31/2022 |
| 英文摘要 | This Design activity will result in a proposal to create a Biology Integration Institute that will synthesize recent advances in wildlife virology and pursue new insights about the ecology and evolution of the global virome. The pandemic emergence of SARS-CoV-2 is only the latest development in an accelerating trend of dangerous viruses emerging from wildlife. Global travel, urbanization, and increasing human-wildlife contact have all made it easier for these viruses to emerge. In the future, climate change and land use change will reassemble the global virome even further, forcing mammals to cross continents, meet in new ecosystems, and exchange viruses thousands of times more, potentially unleashing even more threats to global health. At least 10,000 of these mammal viruses might have the potential to infect humans, but most of the global virome is still undescribed: only about 1% of mammal viruses have been discovered, and a much smaller fraction in other vertebrates. With so little data, it is difficult to predict which viruses will pose a future threat, or where, when, and how they could emerge. Predicting the next pandemic threat will require new data spanning biological scales, from single genes up to deep evolutionary time, and new statistical methods from the cutting edge of computer science and mathematics. In addition, the project will host summer residencies for trainees and develope new coursework that combines biology with hands-on computer science labs. The project assembles a group of virologists, computer scientists, statisticians, and ecologists to explore cutting edge scientific questions about methodology, inference, and impact. The project has three aims: (1) synthesizing existing data about host-virus associations for all vertebrate clades; (2) developing novel approaches to predict host-virus interaction networks, using novel data streams like viral strain diversity characterized from genomes, or receptor data from immunological studies; and (3) developing frameworks for actionable science that will put viral ecology to use for global health science and security. These aims will be accomplished through collaborative workshops. In doing so it will establish a foundation for a full Implementation proposal to develop an Emerging Virus Institute. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. |
| 资助机构 | US-NSF |
| 项目经费 | $166,189.00 |
| 项目类型 | Standard Grant |
| 国家 | US |
| 语种 | 英语 |
| 文献类型 | 项目 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/212018 |
| 推荐引用方式 GB/T 7714 | Colin Carlson.BII-Design: Exploring the ecology and evolution of the global virome with big data and machine learning.2021. |
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