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Big Data approaches to host-pathogen mapping: EID2 - an open-access, taxonomically- and spatially-referenced database of pathogens and their hosts

Big Data approaches to host-pathogen mapping: EID2 - an open-access, taxonomically- and spatially-referenced database of pathogens and their hosts
宿主-病原体绘图的大数据方法:EID2 - 病原体及其宿主的开放访问、分类学和空间参考数据库
批准号:
BB/N02320X/1
负责人:
Matthew Baylis
金额:
$19.23万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --

项目摘要

项目成果

Matthew Baylis的其他基金

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中文摘要
翻译
已知的人类病原体以及与我们关系密切的动物病原体有哪些,因此可能会传播给我们?我们吃的植物的已知病原体都有哪些?这些病原体在世界上的什么地方被发现?公众可能会感到惊讶,这些问题的答案很难获得。最近(2013年)的一项估计是,只有大约五十分之一的人类疾病得到了全面的测绘,而动物和植物疾病的情况可能更糟。近年来,利物浦大学创建了一个人类和动物病原体的开放获取数据库,称为ENHanCED传染病数据库或EID 2。它储存了关于病原体、其宿主以及在世界上国家和次国家(即州或地区)一级发现这两种病原体的信息。所有数据都与证据相关联。输入数据库的数据主要来自三个公开的在线资源:分类数据库(描述病原体或宿主是哪种生物体-病毒、昆虫、哺乳动物等);一个核苷酸序列数据库(提供病原体的宿主和位置信息)和一个名为PubMed的出版物数据库。重要的是,数据是通过自动化程序从这些数据源获得的,因此它们可以定期更新,而工作量相对较小。这一点很重要,因为,例如,进入Genbank的核苷酸序列的数量,我们的信息来源之一,每年接近1000万; PubMed每年索引的新论文超过100万篇(NCBI统计数据)。我们预计EID 2将成为参与健康相关研究的人员和其他健康专业人员的主要资源。EID 2中的数据量已经很大,随着时间的推移,随着更多数据的可用性和自动输入数据库,我们希望它将变得更加全面,并成为病原体/疾病信息的权威来源。确定宿主的病原体,病原体的宿主,特定国家或地区的已知病原体,病原体分布图,该提案的目的是扩大数据库,将作物病原体包括在内,增加一个新的应通报动物疾病数据流,使其更加全面和及时,随着新数据的出现定期更新,提高其功能和速度,允许用户要求更改和下载定制的数据输出,不断评估其准确性,并将其推广到研究和其他社区。
英文摘要
What are all of the known pathogens of humans, and those of the animals that associate closely with us, and hence might spread to us? What are all of the known pathogens of the plants that we eat? And where in the world are these pathogens found? The general public may be surprised that answers to these questions are hard to obtain. A recent (2013) estimate is that only about one in fifty of human diseases have been comprehensively mapped, and the situation for animal and plant diseases is probably worse.In recent years the University of Liverpool has created an open-access database of human and animal pathogens, called the ENHanCED Infectious Diseases database or EID2. It stores information on pathogens, their hosts, and where both are found in the world, at national and sub-national (i.e. state or region) levels. All data are linked to evidence. The data entered into the database is obtained largely from three publicly available online resources: a taxonomy database (which describes which sort of organism a pathogen or host is - virus, insect, mammal etc.); a nucleotide sequence database (which provides information on the hosts and locations of pathogens); and a publication database called PubMed. Importantly, the data is obtained from these data sources by automated procedures, such that they can be regularly updated for relatively little effort. This is important as, for example, the numbers of nucleotide sequences entered into Genbank, one source of our information, is approaching 10 million per year; and there are over 1 million new papers indexed annually by PubMed (NCBI statistics).We expect EID2 to become a major resource for people involved in health-related research, and other health professionals. The volume of data in EID2 is already large and, over time, as more data become available and are automatically entered into the database, we hope it will become more comprehensive, and the definitive source of pathogen/disease information.EID2 offers numerous functions: identifying the pathogens of hosts, the hosts of pathogens, the known pathogens of a specific country or region, maps of the distribution of pathogens, and more besides.The aim of this proposal is to expand the database to include the pathogens of crop plants, add a new data stream for notifiable animal diseases which will make it more comprehensive and timely, update it regularly as new data become available, increase its functionality and speed, allow users to request changes and download bespoke data outputs, continually assess its accuracy, and promote its use to research and other communities.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
Identifying life-history patterns along the fast-slow continuum of mammalian viral carriers
识别哺乳动物病毒携带者快慢连续体的生活史模式
DOI: 10.21203/rs.3.rs-2722217/v1
发表时间: 2023
期刊:
影响因子: --
作者: [Tonelli A]
通讯作者: Tonelli A
Predicting mammalian hosts in which novel coronaviruses can be generated
预测可产生新型冠状病毒的哺乳动物宿主
DOI: 10.1101/2020.06.15.151845
发表时间: 2020
期刊:
影响因子: --
作者: [Wardeh M]
通讯作者: Wardeh M
Reply to Gautret et al.
回复 Gautret 等人。
DOI: 10.1093/infdis/jix022
发表时间: 2017
期刊: The Journal of infectious diseases
影响因子: --
作者: [Caminade C]
通讯作者: Caminade C
DOI: 10.1038/s41598-017-06948-9
发表时间: 2017-08-02
期刊: Scientific reports
影响因子: 4.6
作者: [McIntyre KM, Setzkorn C, Hepworth PJ, Morand S, Morse AP, Baylis M]
通讯作者: Baylis M
共 7 条
    RCG Culex distribution, vector competence and threat of transmission of arboviruses to humans and animals in the UK
    • 批准号:
      BB/X018172/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $125.43万
    • 财政年份:
      2023
    • 负责人:
      Matthew Baylis
    • 依托单位:
    Translation to policy, practice and product for low and middle income countries
    • 批准号:
      EP/T015217/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $83.97万
    • 财政年份:
      2019
    • 负责人:
      Matthew Baylis
    • 依托单位:
    Understanding the emergence of variant infectious bronchitis virus in chickens in UK and India: shared control strategies
    • 批准号:
      BB/P025749/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $3.97万
    • 财政年份:
      2017
    • 负责人:
      Matthew Baylis
    • 依托单位:
    GCRF: One Health Regional Network for the Horn of Africa (HORN)
    • 批准号:
      BB/P027954/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $1006.4万
    • 财政年份:
      2017
    • 负责人:
      Matthew Baylis
    • 依托单位:
    国内基金
    海外基金
    Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
    Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
    Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
    • 批准号:
      --
    • 项目类别:
      --
    • 资助金额:
      40万元
    • 批准年份:
      2020
    • 负责人:
      Vikrant Gupta
    • 依托单位:
    基于Linked Open Data的Web服务语义互操作关键技术
    • 批准号:
      61373035
    • 项目类别:
      面上项目
    • 资助金额:
      77.0万元
    • 批准年份:
      2013
    • 负责人:
      冯志勇
    • 依托单位: