A novel informatics approach to understanding complex muscle fiber phenotypes
一种理解复杂肌纤维表型的新信息学方法
基本信息
- 批准号:8929291
- 负责人:
- 金额:$ 36.04万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2014
- 资助国家:美国
- 起止时间:2014-09-28 至 2018-09-27
- 项目状态:已结题
- 来源:
- 关键词:AccountingAffectAlgorithmsAmyotrophic Lateral SclerosisBecker Muscular DystrophyBioinformaticsBiological MarkersBiological ProcessCardiacCardiomyopathiesCardiopulmonaryCause of DeathCell NucleusCell membraneCellsCellular MembraneClassificationClinicClinicalClinical ResearchCommunitiesComplexComputing MethodologiesData AnalysesData SetDetectionDevelopmentDiagnosisDiseaseDrug KineticsDuchenne muscular dystrophyDyesEndomysiumEnvironmentEvaluationEyeFacioscapulohumeral Muscular DystrophyFiberFunctional disorderHeadHistopathologyHumanHypertrophyImageImage AnalysisInclusion Body MyositisInflammatoryInformaticsInterventionInvestigationJawLabelLaboratoriesLaboratory ResearchLimb structureLocationLungManualsMeasurementMeasuresMembraneMembrane ProteinsMethodsMicroscopicMolecularMotor NeuronsMovementMuscleMuscle CellsMuscle FibersMuscle WeaknessMuscular AtrophyMuscular DystrophiesMyasthenia GravisMyopathyNatural regenerationNeurodegenerative DisordersPathologic ProcessesPathologistPatientsPharmacodynamicsPhenotypePhysiological ProcessesPlayPopulationPositioning AttributeProcessProteinsPublic HealthResearchResearch PersonnelRoleSlideSource CodeStaining methodStainsStructureSurvival RateTechniquesTherapeuticThickTimeTissue SampleTreatment EfficacyVariantaccurate diagnosisbasebehavior testcellular imagingclinical practicedata managementdesigndisease diagnosiseffective therapygraphical user interfaceimage processingimaging agentimprovedinnovationnovelopen sourceperformance testsrelating to nervous systemstatisticstool
项目摘要
DESCRIPTION (provided by applicant): We propose to develop a bioinformatics toolbox to process and quantify complex muscle cell images for automated phenotype analysis. The toolbox is aimed to provide both clinical practitioners and laboratory investigators with the much-needed capability to automatically detect and identify pathological features that manifest themselves in many muscle-related diseases such as cardiomyopathy, muscular hypertrophy, amyotrophic lateral sclerosis (ALS) (often known as Lou Gehrig's disease), muscular dystrophies such as Duchenne muscular dystrophy and Becker muscular dystrophy, and inflammatory muscle damage. Many of these conditions have no effective treatment and high fatality rates. For example, ALS is progressive neurodegenerative disease that is caused by the death of motor neurons and results in increasing muscle weakness and atrophy, has a survival rate less than twenty percent over a five-year period, and the disease affects more 5,000 people in the U.S. each year. In our search for treatment for the muscle-related diseases, lack of computational method to objectively and quantitatively analyze muscle cell images has become a rate limit factor. As clinicians and researchers are increasingly looking into the cellular and molecular mechanisms of the diseases, detailed pathological analysis is necessary for people to understand the biological processes. Yet, the only available approach is manual analysis which is confined to small datasets and qualitatively interpretation of the images. Important pathological features may be missed by manual analysis or obscured due to the large variation in human observation. Also results of manual analysis are not immediately ready for data management and analysis because of the long time it takes. Hence we identified the need for a dedicated toolbox to facilitate muscle-related research, which was confirmed by our user community.
Featuring novel imaging processing algorithms, the toolbox will quantitatively analyze muscle cells, integrate results from multiple channels, and export quantitative results, with little user intervention. The toolbox will advance clinical and laboratory research by providing detailed analysis of histopathological features such as the intact of cellular membrane, the location of nuclei, and geometric measurements of the cells. It will facilitate discovery by highlighting subtl yet important information in histopathology, reducing human errors, and enabling research to analyze a larger number of images than they currently are able to. The toolbox will also improve workflow in clinics and laboratories by providing users with high sensitivity, objectivity, and efficiency in interpreting muscle cell images. The quantifying capability of the toolbox will allow
users to compare therapeutic treatments with a high confidence level.
Overall the project will benefit the large biomedical community of treating and researching muscle-related diseases. In turn, the project will benefit the patients of muscular diseases by facilitating diagnosis of muscular disorders and discovery of new therapies.
描述(由申请人提供):我们建议开发一个生物信息学工具箱来处理和量化复杂的肌肉细胞图像,用于自动表型分析。该工具箱旨在为临床从业人员和实验室研究人员提供急需的功能,以自动检测和识别在许多肌肉相关疾病中表现出来的病理特征,如心肌病、肌肉肥大、肌萎缩侧索硬化症(ALS)(通常称为Lou Gehrig's病)、肌肉营养不良症(如Duchenne肌营养不良症和Becker肌营养不良症)和炎症性肌肉损伤。其中许多病症没有有效治疗,死亡率很高。例如,肌萎缩性侧索硬化症(ALS)是一种由运动神经元死亡引起的进行性神经退行性疾病,其结果是肌肉无力和萎缩加剧,5年内的存活率不到20%,在美国每年有5000多人患有这种疾病。在我们寻求治疗肌肉相关疾病的过程中,缺乏客观、定量分析肌肉细胞图像的计算方法已经成为限制速度的因素。随着临床医生和研究人员越来越多地关注疾病的细胞和分子机制,详细的病理分析对于人们了解生物学过程是必要的。然而,唯一可用的方法是人工分析,这仅限于小数据集和图像的定性解释。重要的病理特征可能会被人工分析遗漏或由于人类观察的巨大变化而模糊不清。此外,手工分析的结果不能立即用于数据管理和分析,因为它需要很长时间。因此,我们确定需要一个专门的工具箱来促进肌肉相关的研究,我们的用户社区也证实了这一点。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Xiaoyin Xu其他文献
Xiaoyin Xu的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Xiaoyin Xu', 18)}}的其他基金
Computer aided diagnosis of cancer metastases in the brain
计算机辅助诊断脑部癌症转移
- 批准号:
9759982 - 财政年份:2016
- 资助金额:
$ 36.04万 - 项目类别:
Computer aided diagnosis of cancer metastases in the brain
计算机辅助诊断脑部癌症转移
- 批准号:
9216187 - 财政年份:2016
- 资助金额:
$ 36.04万 - 项目类别:
A novel informatics approach to understanding complex muscle fiber phenotypes
一种理解复杂肌纤维表型的新信息学方法
- 批准号:
9341379 - 财政年份:2014
- 资助金额:
$ 36.04万 - 项目类别:
A novel informatics approach to understanding complex muscle fiber phenotypes
一种理解复杂肌纤维表型的新信息学方法
- 批准号:
8760564 - 财政年份:2014
- 资助金额:
$ 36.04万 - 项目类别:
相似海外基金
RII Track-4:NSF: From the Ground Up to the Air Above Coastal Dunes: How Groundwater and Evaporation Affect the Mechanism of Wind Erosion
RII Track-4:NSF:从地面到沿海沙丘上方的空气:地下水和蒸发如何影响风蚀机制
- 批准号:
2327346 - 财政年份:2024
- 资助金额:
$ 36.04万 - 项目类别:
Standard Grant
BRC-BIO: Establishing Astrangia poculata as a study system to understand how multi-partner symbiotic interactions affect pathogen response in cnidarians
BRC-BIO:建立 Astrangia poculata 作为研究系统,以了解多伙伴共生相互作用如何影响刺胞动物的病原体反应
- 批准号:
2312555 - 财政年份:2024
- 资助金额:
$ 36.04万 - 项目类别:
Standard Grant
How Does Particle Material Properties Insoluble and Partially Soluble Affect Sensory Perception Of Fat based Products
不溶性和部分可溶的颗粒材料特性如何影响脂肪基产品的感官知觉
- 批准号:
BB/Z514391/1 - 财政年份:2024
- 资助金额:
$ 36.04万 - 项目类别:
Training Grant
Graduating in Austerity: Do Welfare Cuts Affect the Career Path of University Students?
紧缩毕业:福利削减会影响大学生的职业道路吗?
- 批准号:
ES/Z502595/1 - 财政年份:2024
- 资助金额:
$ 36.04万 - 项目类别:
Fellowship
Insecure lives and the policy disconnect: How multiple insecurities affect Levelling Up and what joined-up policy can do to help
不安全的生活和政策脱节:多种不安全因素如何影响升级以及联合政策可以提供哪些帮助
- 批准号:
ES/Z000149/1 - 财政年份:2024
- 资助金额:
$ 36.04万 - 项目类别:
Research Grant
感性個人差指標 Affect-X の構築とビスポークAIサービスの基盤確立
建立个人敏感度指数 Affect-X 并为定制人工智能服务奠定基础
- 批准号:
23K24936 - 财政年份:2024
- 资助金额:
$ 36.04万 - 项目类别:
Grant-in-Aid for Scientific Research (B)
How does metal binding affect the function of proteins targeted by a devastating pathogen of cereal crops?
金属结合如何影响谷类作物毁灭性病原体靶向的蛋白质的功能?
- 批准号:
2901648 - 财政年份:2024
- 资助金额:
$ 36.04万 - 项目类别:
Studentship
ERI: Developing a Trust-supporting Design Framework with Affect for Human-AI Collaboration
ERI:开发一个支持信任的设计框架,影响人类与人工智能的协作
- 批准号:
2301846 - 财政年份:2023
- 资助金额:
$ 36.04万 - 项目类别:
Standard Grant
Investigating how double-negative T cells affect anti-leukemic and GvHD-inducing activities of conventional T cells
研究双阴性 T 细胞如何影响传统 T 细胞的抗白血病和 GvHD 诱导活性
- 批准号:
488039 - 财政年份:2023
- 资助金额:
$ 36.04万 - 项目类别:
Operating Grants
How motor impairments due to neurodegenerative diseases affect masticatory movements
神经退行性疾病引起的运动障碍如何影响咀嚼运动
- 批准号:
23K16076 - 财政年份:2023
- 资助金额:
$ 36.04万 - 项目类别:
Grant-in-Aid for Early-Career Scientists