Cell Modeling
细胞建模
基本信息
- 批准号:10228748
- 负责人:
- 金额:$ 41.31万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-09-24 至 2023-07-31
- 项目状态:已结题
- 来源:
- 关键词:3-DimensionalAddressAlgorithmsArchitectureAutomobile DrivingBiochemicalBiochemical PathwayBiochemistryBiologicalBiological ModelsBrainCell modelCellsCloud ComputingCodeComplexComputer ModelsComputer SimulationCouplingData SetDevelopmentDevelopment PlansElectronsEvaluationEventFunctional disorderFundingGeometryGoalsHigh Performance ComputingHybridsImageInternetIntuitionKnowledgeLanguageLearningMemoryMethodsModelingModificationMolecularNetwork-basedNeurologicNeuronsPathologyPhasePhysicsPreparationProcessPythonsReactionResearchResearch PersonnelResearch Project GrantsRunningScheduleSignal PathwaySignal TransductionSpace ModelsStructureSynapsesSystemTechnologyTimeUpdateVisionWorkadvanced simulationbasebiological systemscell typecomputing resourcesdesignflexibilityimage registrationimprovedinsightmacromolecular assemblymeetingsmicroscopic imagingmodel buildingmodel developmentmodels and simulationmulti-scale modelingmultithreadingneural circuitneurophysiologynext generationparallelizationparticlesimulationsuccesstool
项目摘要
IV. TR&D2 - Abstract
The overall goal of this project is to develop the next generation computer simulation platform for spatially
realistic simulation and analysis of cellular and subcellular biochemistry. Cellular systems, especially in
neurons, are profoundly difficult to understand because of the interplay between spatial, biochemical and
molecular complexity that occurs on multiple levels of organization, from macromolecular assemblies to
synapse architecture to neural circuits. Biological complexity is daunting and scientific investigators must
persevere to finds ways to overcome it. This is important because Scientific Discovery is driven by testable
hypotheses which derive from our intuition and questions surrounding our current understanding of reality. But
when daunting complexity confounds our intuition we struggle to conceive new hypotheses and the cycle of
discovery grinds to a halt. Computational models allow investigators to probe the complex relationships
between biological components, obtain new insights and intuition -- the genesis of new hypotheses. The
MCell/CellBlender platform for cell modeling we are developing is expressly designed to fulfill this need,
providing insight and understanding of complex cellular systems. The cell modeling tools we develop here are
designed to mesh with the molecular, network, and image-derived modeling tools of TR&Ds 1, 3 and 4. The
tools will be used by our Driving Biomedical Project research partners to study neuronal and synaptic structure
and function and the intricate biochemical pathways involved in learning and memory in the brain. The detailed
level of understanding of these systems afforded by computational modeling of these systems will provide new
insights that may be applicable to many types of cell signaling pathways, and in particular should help to
elucidate how dysfunctions in cell signaling may contribute to neurological and psychiatric pathology.
四. TR&D2 -摘要
该项目的总体目标是开发下一代空间计算机仿真平台,
细胞和亚细胞生物化学的真实模拟和分析。蜂窝系统,特别是在
神经元,是深刻的难以理解的,因为空间,生化和
分子复杂性,发生在多个层次的组织,从大分子组装,
神经回路的突触结构。生物学的复杂性令人望而生畏,科学研究人员必须
坚持找到克服它的方法。这很重要,因为科学发现是由可测试的
这些假设来自我们的直觉和围绕我们目前对现实的理解的问题。但
当令人生畏的复杂性混淆了我们的直觉时,我们努力构思新的假设,
发现号慢慢停了下来计算模型使研究人员能够探索复杂的关系
在生物成分之间,获得新的见解和直觉-新假设的起源。的
我们正在开发的用于细胞建模的MCell/CellBlender平台就是专门为满足这一需求而设计的,
提供对复杂细胞系统的洞察和理解。我们在这里开发的细胞建模工具是
旨在与TR& D 1,3和4的分子,网络和图像衍生建模工具相结合。的
我们的驱动生物医学项目研究合作伙伴将使用这些工具来研究神经元和突触结构
和功能以及复杂的生物化学途径参与大脑的学习和记忆。的详细
通过对这些系统的计算建模,对这些系统的理解水平将提供新的
这些见解可能适用于许多类型的细胞信号传导途径,特别是应该有助于
阐明细胞信号传导功能障碍如何导致神经和精神病理学。
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 }}
TERRENCE J SEJNOWSKI其他文献
TERRENCE J SEJNOWSKI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('TERRENCE J SEJNOWSKI', 18)}}的其他基金
DDALAB: Identifying Latent States from Neural Recordings with Nonlinear Causal Analysis
DDALAB:通过非线性因果分析从神经记录中识别潜在状态
- 批准号:
10643212 - 财政年份:2023
- 资助金额:
$ 41.31万 - 项目类别:
Multiscale modeling and large-scale recordings of trauma-induced epileptogenesis
创伤诱发癫痫发生的多尺度建模和大规模记录
- 批准号:
9789979 - 财政年份:2018
- 资助金额:
$ 41.31万 - 项目类别:
Multiscale modeling and large-scale recordings of trauma-induced epileptogenesis
创伤诱发癫痫发生的多尺度建模和大规模记录
- 批准号:
10229375 - 财政年份:2018
- 资助金额:
$ 41.31万 - 项目类别:
Multiscale modeling and large-scale recordings of trauma-induced epileptogenesis
创伤诱发癫痫发生的多尺度建模和大规模记录
- 批准号:
10468022 - 财政年份:2018
- 资助金额:
$ 41.31万 - 项目类别:
Multiscale modeling and large-scale recordings of trauma-induced epileptogenesis
创伤诱发癫痫发生的多尺度建模和大规模记录
- 批准号:
9597206 - 财政年份:2018
- 资助金额:
$ 41.31万 - 项目类别:
SIMULATION NEUROTRANSMITTER DIFFUSION IN CEREBELLAR GLOMERULI
模拟小脑肾小球中的神经递质扩散
- 批准号:
7956214 - 财政年份:2009
- 资助金额:
$ 41.31万 - 项目类别:
Intrinsic and synaptic mechanisms of epileptogenesis triggered by cortical trauma
皮质创伤引发癫痫发生的内在机制和突触机制
- 批准号:
8144893 - 财政年份:2009
- 资助金额:
$ 41.31万 - 项目类别:
Intrinsic and synaptic mechanisms of epileptogenesis triggered by cortical trauma
皮质创伤引发癫痫发生的内在机制和突触机制
- 批准号:
8318223 - 财政年份:2009
- 资助金额:
$ 41.31万 - 项目类别:
Intrinsic and synaptic mechanisms of epileptogenesis triggered by cortical trauma
皮质创伤引发癫痫发生的内在机制和突触机制
- 批准号:
7654250 - 财政年份:2009
- 资助金额:
$ 41.31万 - 项目类别:
相似海外基金
Rational design of rapidly translatable, highly antigenic and novel recombinant immunogens to address deficiencies of current snakebite treatments
合理设计可快速翻译、高抗原性和新型重组免疫原,以解决当前蛇咬伤治疗的缺陷
- 批准号:
MR/S03398X/2 - 财政年份:2024
- 资助金额:
$ 41.31万 - 项目类别:
Fellowship
Re-thinking drug nanocrystals as highly loaded vectors to address key unmet therapeutic challenges
重新思考药物纳米晶体作为高负载载体以解决关键的未满足的治疗挑战
- 批准号:
EP/Y001486/1 - 财政年份:2024
- 资助金额:
$ 41.31万 - 项目类别:
Research Grant
CAREER: FEAST (Food Ecosystems And circularity for Sustainable Transformation) framework to address Hidden Hunger
职业:FEAST(食品生态系统和可持续转型循环)框架解决隐性饥饿
- 批准号:
2338423 - 财政年份:2024
- 资助金额:
$ 41.31万 - 项目类别:
Continuing Grant
Metrology to address ion suppression in multimodal mass spectrometry imaging with application in oncology
计量学解决多模态质谱成像中的离子抑制问题及其在肿瘤学中的应用
- 批准号:
MR/X03657X/1 - 财政年份:2024
- 资助金额:
$ 41.31万 - 项目类别:
Fellowship
CRII: SHF: A Novel Address Translation Architecture for Virtualized Clouds
CRII:SHF:一种用于虚拟化云的新型地址转换架构
- 批准号:
2348066 - 财政年份:2024
- 资助金额:
$ 41.31万 - 项目类别:
Standard Grant
BIORETS: Convergence Research Experiences for Teachers in Synthetic and Systems Biology to Address Challenges in Food, Health, Energy, and Environment
BIORETS:合成和系统生物学教师的融合研究经验,以应对食品、健康、能源和环境方面的挑战
- 批准号:
2341402 - 财政年份:2024
- 资助金额:
$ 41.31万 - 项目类别:
Standard Grant
The Abundance Project: Enhancing Cultural & Green Inclusion in Social Prescribing in Southwest London to Address Ethnic Inequalities in Mental Health
丰富项目:增强文化
- 批准号:
AH/Z505481/1 - 财政年份:2024
- 资助金额:
$ 41.31万 - 项目类别:
Research Grant
ERAMET - Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
ERAMET - 快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10107647 - 财政年份:2024
- 资助金额:
$ 41.31万 - 项目类别:
EU-Funded
Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10106221 - 财政年份:2024
- 资助金额:
$ 41.31万 - 项目类别:
EU-Funded
Recite: Building Research by Communities to Address Inequities through Expression
背诵:社区开展研究,通过表达解决不平等问题
- 批准号:
AH/Z505341/1 - 财政年份:2024
- 资助金额:
$ 41.31万 - 项目类别:
Research Grant