DiseaseNetMiner - A novel tool for mining integrated biological networks of host and pathogen interaction
疾病NetMiner - 一种挖掘宿主和病原体相互作用的综合生物网络的新工具
基本信息
- 批准号:BB/N022874/1
- 负责人:
- 金额:$ 16.37万
- 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
- 起止时间:2016 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Modern society is increasingly under threat from a plethora of microscopic fungal pathogens, which cause diseases in agricultural and horticultural crops, and in farmed animals. Many of these diseases cause a significant, detrimental impact on global and local food security. Furthermore, there is a worrying tendency for pathogens to become more aggressive towards their hosts, to cause more disease (increased virulence) and for the anti-fungal chemicals (called fungicides) that are often used to control fungal pathogen outbreaks to become less effective. In the recent past, (during the genomics era) scientists have developed technologies to sequence and assemble all the chromosomes of an organisms and predict the gene content (i.e. obtain their complete genome blueprints). Now, in the post-genomic era, next generation sequencing technologies have been developed and this has led to an explosion of more genomic data alongside a wealth of gene expression, protein expression, genetic and biological data, which are used by scientists to describe pathogen-host interaction phenotypes and disease outcomes. However, for many scientists with expertise in biology, biochemistry or genetics, this 'omics' data explosion is often seen as a burden, 'an infinite data soup of varying qualities' that only those with specialist computing-based interpretation skills (called bioinformatics), but often only minimal specialist biological knowledge, can penetrate. Therefore, new computer based tools urgently need to be developed to allow researchers to connect, explore and compare all the large and small-scale datasets available for pathogenic species that cause diseases. Once we fully understand how fungal pathogens cause disease, and how the host species try to defend themselves, will it be possible to manipulate these processes and mechanisms and go on to devise new ways to reduce disease levels and thereby improve global food security. In this project, we will develop a novel software tool, called DiseaseNetMiner, which will be user-friendly and can be used by many different types of scientists to explore integrated biological networks that can predict processes controlling the disease-causing abilities of fungal pathogens. DiseaseNetMiner will deliver understandable outputs from diverse and complex large-scale data inputs. DiseaseNetMiner will allow researchers without specialist bioinformatics skill to explore and compare this wealth of existing data from multiple species with their own latest cutting-edge results to permit rapid progress and new discoveries. This fundamental tool will effectively connect different data types and then return the results in an accessible, explorable, as well as scalable, format that can be easily manipulated, displayed and interrogated. DiseaseNetMiner will create a novel research environment from which new scientific insights and biological discoveries can be made.The UK research community has been at the very forefront of research and discovery in this field. The initiative we propose will be an exceptionally useful and cost-effective way of ensuring that the leadership shown by the UK research community will continue in the decade ahead. We expect this to yield outcomes with huge impact in our field and beyond, to meet the grand challenges of our age.
现代社会越来越受到过多的微观真菌病原体的威胁,这些病原体导致农业和园艺作物以及养殖动物的疾病。其中许多疾病对全球和地方粮食安全造成重大的有害影响。此外,令人担忧的趋势是,病原体对宿主更具侵略性,导致更多疾病(毒性增加),并且通常用于控制真菌病原体爆发的抗真菌化学品(称为杀真菌剂)变得不那么有效。在最近的过去,(在基因组学时代)科学家已经开发出了对生物体的所有染色体进行测序和组装并预测基因内容(即获得其完整的基因组蓝图)的技术。现在,在后基因组时代,下一代测序技术已经开发出来,这导致了更多基因组数据的爆炸,以及丰富的基因表达,蛋白质表达,遗传和生物学数据,科学家使用这些数据来描述病原体-宿主相互作用表型和疾病结果。然而,对于许多具有生物学、生物化学或遗传学专业知识的科学家来说,这种“组学”数据爆炸通常被视为一种负担,“一种具有不同质量的无限数据汤”,只有那些具有专业的基于计算的解释技能(称为生物信息学)的科学家,但通常只有最少的专业生物学知识,才能渗透。因此,迫切需要开发新的基于计算机的工具,使研究人员能够连接,探索和比较所有可用于致病物种的大型和小型数据集。一旦我们完全了解真菌病原体如何引起疾病,以及宿主物种如何试图保护自己,就有可能操纵这些过程和机制,并继续设计新的方法来降低疾病水平,从而改善全球粮食安全。在这个项目中,我们将开发一个新的软件工具,称为DiseaseNetMiner,它将是用户友好的,可以被许多不同类型的科学家用来探索集成的生物网络,可以预测控制真菌病原体致病能力的过程。DiseaseNetMiner将从多样化和复杂的大规模数据输入中提供可理解的输出。DiseaseNetMiner将允许没有专业生物信息学技能的研究人员探索和比较来自多个物种的现有数据与他们自己的最新前沿结果,以允许快速进展和新发现。这个基础工具将有效地连接不同的数据类型,然后以可访问、可探索和可扩展的格式返回结果,这些格式可以轻松地操作、显示和查询。DiseaseNetMiner将创造一个新的研究环境,从中可以获得新的科学见解和生物学发现。英国研究界一直处于该领域研究和发现的最前沿。我们提出的倡议将是一个非常有用和具有成本效益的方式,以确保英国研究界所表现出的领导地位将在未来十年继续下去。我们希望这将产生在我们的领域和超越的巨大影响的结果,以满足我们这个时代的巨大挑战。
项目成果
期刊论文数量(9)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species
KnetMiner:支持跨物种基于证据的基因发现和复杂性状分析的综合方法
- DOI:10.1101/2020.04.02.017004
- 发表时间:2020
- 期刊:
- 影响因子:0
- 作者:Hassani-Pak K
- 通讯作者:Hassani-Pak K
Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes.
- DOI:10.1515/jib-2016-0002
- 发表时间:2017-06-13
- 期刊:
- 影响因子:1.9
- 作者:Hassani-Pak K;Rawlings C
- 通讯作者:Rawlings C
A roadmap for gene functional characterisation in wheat
小麦基因功能表征路线图
- DOI:10.7287/peerj.preprints.26877v1
- 发表时间:2018
- 期刊:
- 影响因子:0
- 作者:Adamski N
- 通讯作者:Adamski N
Towards FAIRer Biological Knowledge Networks Using a Hybrid Linked Data and Graph Database Approach.
- DOI:10.1515/jib-2018-0023
- 发表时间:2018-08-07
- 期刊:
- 影响因子:1.9
- 作者:Brandizi M;Singh A;Rawlings C;Hassani-Pak K
- 通讯作者:Hassani-Pak K
Developing integrated crop knowledge networks to advance candidate gene discovery.
- DOI:10.1016/j.atg.2016.10.003
- 发表时间:2016-12
- 期刊:
- 影响因子:0
- 作者:Hassani-Pak, Keywan;Castellote, Martin;Esch, Maria;Hindle, Matthew;Lysenko, Artem;Taubert, Jan;Rawlings, Christopher
- 通讯作者:Rawlings, Christopher
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Keywan Hassani-Pak其他文献
Keywan Hassani-Pak的其他文献
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