Quantitative Neurostatistics

定量神经统计学

• 批准号: 7917200
• 负责人: Daijin Ko
• 金额: $ 11.53万
• 依托单位: UNIVERSITY OF TEXAS SAN ANTONIO
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7917200
• 关键词: Address; Advisory Committees; Biological; Biometry; Cell model; Collaborations; Communities; Complex; Consultations; Data; Data Analyses; Data Set; Doctor of Philosophy; Educational workshop; Experimental Designs; Faculty; Genomics; Glean; Image; Individual; Laboratories; Language; Learning; Measurement; Methodology; Methods; Modeling; Neurobiology; Neurosciences; Participant; Research; Research Personnel; Resources; Science; Statistical Methods; Students; Surface; Synapses; Techniques; Texas; Training; Universities; Work; base; design; interest; meetings; member; programs; research study; statistics; theories; tool; training project

Statistics has greatly influenced all scientific research in the modern era. As new theories are proposed, Statistics comes to the forefront of the debate to quantify how well theory corresponds with observed information. Biologicial research is built upon such observations and modern science is built upon models (e.g., synaptic or cellular models), which closely predict such phenomena . As variability is inherent to all measurements, statistical methods are essential tools for sifting interpretive potential from observations. While many investigators are adept at identifying critical research questions and generating complex data sets, intrinsic information in data is often lost, overlooked, or misinterpreted due to limitations in either the designed experiment or the investigator's repertoire of inferential techniques. Under the "Quantitative Neurobiology" theme of this proposal, a Quantitative Statistics Core will be established to optimize information gleaned from numerical data by providing cutting edge statistical and analytic support to UTSA Neurobiologists during the planning and analysis of their research. The Quantitative Statistics Core supplements the research programs of SNRP-investigators with support in the form of statistical and computational expertise by drawing upon the considerable resources of the PhD program in Applied Biostatistics at UTSA. Three advanced PhD students in Applied Biostatistcs will be chosen based on background and interest to be stationed in the labs of the three SNRP-investigators. Each student will provide ongoing, individualized consultation and collaboration in experimental design and data analytic methods to the investigator's research program. This arrangement will provide Biostatistics PhD students with data for their doctoral projects and training in practical Neuroscience, in addition to adding quanititative power to the research programs of the SNRP-investigators.

统计学极大地影响了现代的所有科学研究。随着新理论的提出， 统计学走到了辩论的前列，量化了理论与观测的一致性 信息。生物学研究建立在这种观察的基础上，现代科学建立在模型的基础上。 (例如，突触或细胞模型)，这些模型可以很好地预测这种现象。因为可变性是所有人固有的 测量，统计方法是从观测中筛选解释潜力的基本工具。 虽然许多研究人员擅长识别关键的研究问题和生成复杂的数据 集合，数据中的内在信息通常会丢失、被忽略或被误解，这是由于 设计性实验或研究人员的全部推理技术。在“数量”项下 《神经生物学》这一主题的建议，将建立一个量化统计核心来优化 通过为UTSA提供前沿的统计和分析支持，从数字数据中收集信息 神经生物学家在规划和分析他们的研究期间。定量统计的核心 为SNRP-调查员的研究方案提供统计和数据支持 通过利用应用型博士项目的大量资源获得计算专业知识 UTSA的生物统计学。应用生物统计学专业的三名高级博士生将根据 背景和兴趣将驻扎在SNRP的三名调查员的实验室。每个学生都会 在实验设计和数据分析方面提供持续的个性化咨询和协作 研究人员的研究计划的方法。这一安排将为生物统计学博士生提供 他们的博士项目和实用神经科学培训的数据，除了添加定量的 对SNRP-调查人员的研究计划的权力。