2011 CSHL GENOME INFORMATICS CONFERENCE
2011 CSHL GENOME INFORMATICS CONFERENCE
批准号:
8204325
负责人:
DAVID J. STEWART
金额:
$3.1万
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-08-08 至 2012-07-31
关键词:
AlgorithmsAmericanAreaAsiansBioinformaticsBiologicalBiologyCommunitiesComputer softwareComputersDataData SetData Storage and RetrievalDevelopmentDisciplineEnsureEnvironmentEuropeanExpert SystemsExplosionFacultyFeesFosteringGenomeGenome engineeringGenomicsGoalsHome environmentImageImageryInformaticsInstitutesInternationalJointsLaboratoriesLength of StayMolecularMolecular BiologyOntologyOralOrganismParticipantPathogenesisPlayPostdoctoral FellowPrincipal InvestigatorProcessPublicationsPublished CommentResearchResearch InstituteResearch PersonnelResourcesScheduleScienceScientistSeasonsSelection CriteriaSenior ScientistSeriesSoftware EngineeringStudentsSystemTechnologyTrustWomanWorkabstractingbasecomparativedata modelingdatabase designdesigngenome databasegraduate studentinterestlecturesmeetingsmicrobialnovelposterssoftware systemssuccesssymposiumtoolunpublished worksvirtual
中文摘要
描述(由申请者提供):冷泉港基因组信息学实验室会议将重点讨论大规模基因组数据和注释的提供和利用。基因组资源在分子水平上提供了对越来越多的生物体的基本描述。这次会议是每年在美国冷泉港和英国欣克斯顿之间交替举行的系列会议的一部分,该系列会议的目标是探索这些资源的最新供应,或许最重要的是,探索它们作为生物发现引擎的用途。这包括存储数据及其相关的数据模型,设计有效的算法来发现这些数据集的不明显的方面,到本体论来简明地描述生物信息,以及支持管理、可视化和探索的软件系统。会议还讨论了基因组学与各种成像应用的结合使用,以及基于基因组学理解微生物发病机制的最新尝试。该会议在过去几年中扩大了其职权范围,以确保它与信息学的最新应用保持同步,同时确保对生物信息学的强烈关注。这次会议汇聚了这个不断增长的领域中的一些领先科学家,我们强烈鼓励来自其他大型信息处理学科的研究人员参加。
与公共卫生相关:在过去十年中,基因组信息的爆炸性增长对计算生物学家提出了一个巨大的挑战,即如何管理这些信息并使其有意义和有用。如果不集中讨论各种不同的方法来处理这些信息,以确保它可以应用于不同的物种、系统和规模,这些数据就有被孤立在虚拟孤岛中的危险,在那里它的用处要小得多。冷泉港基因组信息学实验室会议将重点讨论大规模基因组数据和注释的提供和使用。基因组资源在分子水平上提供了对越来越多的生物体的基本描述。该系列的目标是探索这些资源的最新供应,或许最重要的是,它们作为生物发现的引擎的使用。这包括存储数据及其相关的数据模型,设计有效的算法来发现这些数据集的不明显的方面,到本体论来简明地描述生物信息,以及支持管理、可视化和探索的软件系统。
英文摘要
DESCRIPTION (provided by applicant): The Cold Spring Harbor Laboratory conference on Genome Informatics will focus on the provision and utilization of large scale genomic data and annotations. Genomic resources provide the fundamental descriptions of an increasing array of organisms at the molecular level. This meeting forms part of a series that alternates annually between Cold Spring Harbor, USA and Hinxton, UK, The goal of the series is to explore both the latest provision of these resources, and perhaps most importantly, their use as engines of biological discovery. This ranges from the storage of data and their associated data models, to the design of effective algorithms to uncover non-obvious aspects of these datasets, to ontologies to concisely describe biological information, and software systems to support curation, visualization, and exploration. The conference also covers the use of genomics in combination with various imaging applications and the latest attempts to understand microbial pathogenesis based on genomics. The conference has expanded its remit over the last few years, to ensure it remains current with the latest applications of informatics, all the while ensuring a strong focus on biological informatics. The conference brings together some of the leading scientists in this growing field, and we strongly encourage researchers from other large scale information handling disciplines to attend.
PUBLIC HEALTH RELEVANCE: The explosion of genomic information in the past decade poses an enormous challenge to computational biologists in how to manage this information and render it meaningful and useful. Without intense discussion of a variety of different approaches to handling this information to ensure that it can be applied across diverse species, systems and scales, the data is in danger of being isolated in virtual silos where it is much less useful. The Cold Spring Harbor Laboratory conference on Genome Informatics will focus on the provision and use of large scale genomic data and annotations. Genomic resources provide the fundamental descriptions of an increasing array of organisms at the molecular level. The goal of the series is to explore both the latest provision of these resources, and perhaps most importantly, their use as engines of biological discovery. This ranges from the storage of data and their associated data models, to the design of effective algorithms to uncover non-obvious aspects of these datasets, to ontologies to concisely describe biological information, and software systems to support curation, visualization, and exploration.
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