Computational Modeling Core

计算建模核心

基本信息

批准号：
10551707
负责人：
Aaron Samuel Meyer
金额：
$ 22.77万
依托单位：
LUNDQUIST INSTITUTE FOR BIOMEDICAL INNOVATION AT HARBOR-UCLA MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-08-10 至 2028-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10551707
关键词：
3-Dimensional Age Antibiotics Biological Models Candida albicans Clinical Cohort Studies Collaborations Communities Computational algorithm Computer Models Coupled Data Data Set Development Dimensions Effectiveness Epigenetic Process Experimental Models Gene Expression Genes Genetic Genetic Transcription Healthcare Human Immune Evasion Immune response Immunologics In Vitro Individual Infection Lead Life Longitudinal Studies Machine Learning Measurement Methodology Methods Methylation Modeling Molecular Molecular Profiling Multiomic Data Mus Natural Immunity Nature Noise Organism Outcome Pattern Pharmaceutical Preparations Phenotype Physiological Processes Principal Component Analysis Property Proteomics Research Personnel Sampling Sepsis Series Staphylococcus aureus System Systems Analysis Techniques Technology Testing Time Training Treatment outcome Variant Visualization Work cohort cytokine data integration data modeling data reduction dynamic system effective therapy epigenomics improved individual patient methicillin resistant Staphylococcus aureus mortality mouse model novel outcome prediction pathogen permissiveness predictive modeling primary outcome response sex tool transcriptome sequencing transcriptomics

项目摘要

SUMMARY/ABSTRACT The Computational & Predictive Modeling Core (CPM) will provide state-of-the-art machine learning and data integration methodologies to enable the analysis, interpretation, and predictive modeling of the data created within the other Cores and Projects. To accomplish this, the Core will: (i) develop novel computational modeling frameworks towards predictive modeling of physiological processes with a multi-scale understanding of outcomes, (ii) adapt and combine existing analysis techniques for use in the proposed studies, and (iii) work closely with the other investigators to apply and then interpret the analysis results derived during the proposed studies. A particular focus of the Core’s new methodologic development and modeling applications will be multi-omic data integration across three dimensions: between molecular profiling technologies, across cohort studies, and between experimental models and human infection. These activities will occur in close collaboration with each Project, as evidenced by the Core’s involvement in nearly every Aim of the proposal.

摘要/摘要计算和预测建模核心（CPM）将提供最先进的机器学习和数据集成方法可实现数据的分析，解释和预测建模在其他核心和项目中创建。为此，核心将：（i）开发新颖的计算建模框架以多尺度的理解为实体过程进行预测建模结果，（ii）适应并结合了现有的分析技术，用于拟议的研究，以及（iii）工作与其他研究人员紧密申请，然后解释提议期间得出的分析结果研究。核心新的方法论开发和建模应用程序的特别重点将是跨三个维度的多摩尼克数据整合：分子分析技术之间，整个队列研究以及实验模型和人类感染之间。这些活动将结束与每个项目的合作，核心几乎参与提案的每个目标都证明了这一点。