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相关概念视频

The Scientific Method01:32

The Scientific Method

223.2K
The scientific method is a detailed, empirical problem-solving process used by biologists and other scientists. This iterative approach involves formulating a question based on observation, developing a testable potential explanation for the observation (called a hypothesis), making and testing predictions based on the hypothesis, and using the findings to create new hypotheses and predictions.
Generally, predictions are tested using carefully-designed experiments. Based on the outcome of these...
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The Evidence for Evolution02:55

The Evidence for Evolution

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Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.
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Free Energy01:21

Free Energy

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Free energy—abbreviated as G for the scientist Gibbs who discovered it—is a measurement of useful energy that can be extracted from a reaction to do work. It is the energy in a chemical reaction that is available after entropy is accounted for. Reactions that take in energy are considered endergonic and reactions that release energy are exergonic. Plants carry out endergonic reactions by taking in sunlight and carbon dioxide to produce glucose and oxygen. Animals, in turn, break...
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Additional Subnuclear Structures02:10

Additional Subnuclear Structures

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The eukaryotic nucleus is a double membrane-bound organelle that contains nearly all of the cell’s genetic material in the form of chromosomes. It is rightly called the “brain” of the cell as it shoulders the responsibility of responding to various physiological processes, stress, altered metabolic conditions, and other cellular signals. 
The nucleus contains many membrane-less subnuclear organelles or nuclear bodies, such as nucleoli, Cajal bodies, speckles,...
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Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Next-generation Sequencing03:00

Next-generation Sequencing

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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
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相关实验视频

Updated: May 21, 2025

A New Ex Vivo Model for the Evaluation of Endoscopic Submucosal Injection Material Performance
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A New Ex Vivo Model for the Evaluation of Endoscopic Submucosal Injection Material Performance

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一个新的基于p值的多重测试程序,用于通用线性模型.

Joseph Rilling1, Cheng Yong Tang1

  • 1Department of Statistics, Operations, and Data Science, Temple University, Philadelphia, PA 19122 USA.

Statistics and computing
|March 19, 2025
PubMed
概括
此摘要是机器生成的。

本研究提出了一种新的p值方法,用于一般化的线性模型,以控制依赖测试的错误发现率 (FDR). 它提供了一个灵活的统计框架和高效的算法,用于强大的多重测试.

关键词:
错误发现率 错误发现率模特-X的仿制品 模特-X的仿制品配对估计器是对的估计器.随机行排列的随机排列方式.基于p值的多重测试.

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相关实验视频

Last Updated: May 21, 2025

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A New Ex Vivo Model for the Evaluation of Endoscopic Submucosal Injection Material Performance

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科学领域:

  • 统计 统计 统计 统计
  • 统计建模 统计建模
  • 计算统计学 计算统计学

背景情况:

  • 通用线性模型 (GLMs) 广泛使用,但由于异质变异和参数依赖性,在多重测试中面临挑战.
  • 当前的方法在测试统计数据任意依赖时,难以控制错误发现率 (FDR).

研究的目的:

  • 为GLMs开发一种基于p值的多重测试方法.
  • 为了应对在任意依赖结构下控制FDR的挑战.
  • 提供具有高效计算算法的多功能统计框架.

主要方法:

  • 为GLM开发基于p值的多重测试框架.
  • 整合用于模型矩阵构建的工具,包括随机行顺序和模型X模仿.
  • 解决二次矩阵方程的高效算法,用于构建配对的p值,适合两步测试程序.

主要成果:

  • 拟议的方法有效地控制在特定水平的错误发现率 (FDR).
  • 理论分析证实了新方法的理想特性.
  • 经验评估表明,在各种模拟场景中表现强.

结论:

  • 这种基于p值的新方法为通用线性模型中的多重测试提供了强大的解决方案.
  • 开发的框架和算法提高了FDR控制在复杂的统计环境中的适用性.
  • 这种方法为研究人员在GLM中使用依赖测试统计工作提供了有价值的工具.