Extending InterMine to yeast rat and zebrafish model organism databases
Extending InterMine to yeast rat and zebrafish model organism databases
批准号:
7800145
负责人:
J. Michael Cherry
金额:
$13.54万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-03-26 至 2011-02-28
关键词:
AddressAgingAnimal ModelAppearanceAreaBehaviorBehavioralBiologicalBiologyBiomedical ResearchC. elegans genomeCellular biologyCodeCollaborationsCommitCommunitiesComputer softwareCustomDNADNA SequenceDataData CollectionData SetData SourcesDatabasesDevelopmentDevelopmental BiologyDiseaseDocumentationDrosophila genusElementsEventFundingFutureGene ProteinsGeneric DrugsGenesGenomeGenomicsHealthHealthcareHumanHuman DevelopmentHuman GenomeIndiumInformation NetworksInternetLeadLearningLicensingMiningMolecular GeneticsNematodaNeurologicOntologyOperative Surgical ProceduresOregonOrganismPhysiologyPreventionProcessQuantitative Trait LociRattusResearchResearch InfrastructureSaccharomycesSaccharomycetalesScientistServicesSiteSpecialistSystemUniversitiesWisconsinWorkYeastsZebrafishacronymsbasedata exchangedesigndisease diagnosisflexibilitygenome databasegenome sequencinghigh standardimprovedinteroperabilitymedical schoolsmembermodel organisms databasesopen sourceoutcome forecastpublic health relevancerat genomeresearch studysoftware developmentsuccesstool
中文摘要
描述(申请人提供):在模型生物上进行实验是生物医学研究的基础。其中最重要的三个是发芽酵母(基础研究)、大鼠(药理学、行为学和神经学研究)和斑马鱼(发育、神经学和毒理学研究)。已经建立了捕捉和管理关于这些模式生物的丰富数据的数据库,统称为模式生物数据库(MODS)。现代生物学已经产生了人类以及这些模式生物的完整DNA序列(‘基因组’)。反过来,这又导致了一个新的研究时代,在整个基因组范围内进行实验。基因组学的成功引发了一项挑战,即如何将基因组数据集整合到MODS中,以便所有科学家都可以灵活地查询和提取数据,而不仅仅是被称为生物信息学家的专家,尽管为生物信息学家提供强大的工具也很重要。作为支持另一种模式生物--果蝇的先前工作的一部分,开发了Intermine软件,以极大地提高科学家利用基因组数据的能力和灵活性。Intermine的设计目的是很容易地将其应用于生物学和生物体的其他领域。事实上,它目前正被用于管理NIH资助的modENCODE项目的数据,该项目正在试验性地表征果蝇和线虫模式生物的整个基因组。该项目的目的是将Intermine软件应用于三种MOD:萌芽酵母、老鼠和斑马鱼。这为每个数据库提供了许多优势:它们的用户群体需要但尚未获得的功能;MOD之间的标准接口和一套功能;不同MOD之间的互操作机会,提供了一种工具来比较和对比这组生物体之间的基因和蛋白质的行为,这是今天通常不具备的特征。该项目将在开发英国剑桥Intermine的团队和开发和维护三种MOD的团队之间进行合作,这些团队分别位于斯坦福大学(YYEE,SGD)、威斯康星医学院(RAT,RGD)和俄勒冈大学(斑马鱼,ZFIN)。这项提议为每个站点提供一名工作人员,由此产生的小组将共同努力,将数据转移到Intermine数据库,并向其中添加分析工具,这些数据库将整合在每个国防部站点及其用户界面中。以这种方式合作的一个好处是,一个地点的开发可以立即惠及其他地点。到项目结束时,国防部将能够为他们的研究社区提供更大的功能,更广泛的社区将免费获得对支持Intermine软件的改进。拟议的项目在整合主要模式生物的实验结果方面是独一无二的。这种整合对于我们深入了解分子遗传学、细胞生物学、发育生物学、生理学,以及最重要的人类健康和疾病是至关重要的。公共卫生相关性:最近对人类基因组序列的解码通过提高对人类发育、功能、衰老和疾病的理解,对人类医疗保健的未来产生了前所未有的影响。然而,为了充分了解这些事件而必须做的大部分实验工作不能在人类身上完成,因此必须在所谓的模式生物中进行。拟议的项目将解决一个迫切需要,即提高对正在生成的大量模型生物数据进行整合、分析和比较的效率,这将导致对人类的更好了解,从而更好地诊断、预测、预防和治愈疾病。
英文摘要
DESCRIPTION (provided by applicant): Conducting experiments on model organisms is fundamental to biomedical research. Three of the most important are budding yeast (fundamental studies), rat (pharmacological, behavioral and neurological studies) and zebrafish (developmental, neurological and toxicological studies). Databases to capture and curate the wealth of data on these model organisms have been established and are known collectively as Model Organism Databases (MODs). Modern biology has resulted in the complete DNA sequence (`genome') of the human as well as these model organisms. In turn this has led to a new era of research in which experiments are carried out at the whole genome scale. The success of genomics has fuelled a challenge to integrate genomic datasets within the MODs in such a way that querying them and extracting data in a flexible fashion is possible for all scientists; not just specialists known as bioinformaticians, although it is also important to provide bioinformaticians with powerful tools. As part of previous work in support of another model organism, the fruitfly, InterMine software was developed to greatly increase the power and flexibility with which scientists can utilize genomic data. InterMine was designed to be applied easily to other areas of biology and organisms. Indeed it is currently being used to manage data from the NIH-funded modENCODE project which is experimentally characterizing the entire genomes of the fruitfly and nematode model organisms. The aim of this project is to apply the InterMine software to three MODs: budding yeast, rat and zebrafish. This provides a number of advantages to each database: functionality that their user communities demand but that are not yet available; a standard interface and set of functionality between MODs; an opportunity for the different MODs to inter-operate providing a tool to compare and contrast the behavior of genes and proteins between this set of organisms, a feature that is not generally available today. This project will be carried out as a collaboration between the team that developed InterMine, based in Cambridge UK, and the teams that develop and maintain the three MODs, based at Stanford University (yeast, SGD), the Medical College of Wisconsin (rat, RGD) and the University of Oregon (zebrafish, ZFIN). This proposal provides one staff member per site, and the resulting team will work together to transfer data into, and add analysis tools to, InterMine databases that will be integrated at each MOD site and within their user interfaces. A benefit of working together in this way is that developments at one site can immediately benefit the others. By the end of the project the MODs will be able to provide far greater functionality to their research communities, and improvements to the underpinning InterMine software will be freely available to the broader community. The proposed project is unique in its integration of experimental results across the major model organisms. This integration is essential for our advanced understanding of molecular genetics, cell biology, developmental biology, physiology, and most importantly, human health and disease. PUBLIC HEALTH RELEVANCE: The recent decoding of the human genome sequence has unprecedented implications for the future of human healthcare through improved understanding of human development, functioning, aging and disease. However, much of the experimental work that has to be done to fully understand these events cannot be done in humans and must therefore be carried out in so-called model organisms. The proposed project will address a pressing need to improve the efficiency with which the huge amounts of Model Organism data being generated can be integrated, analysed and compared, which will lead to improved understanding of humans and thus to better disease diagnosis, prognosis, prevention and cure.
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