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相关概念视频

Cluster Sampling Method01:20

Cluster Sampling Method

11.6K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
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Per-Unit Sequence Models01:26

Per-Unit Sequence Models

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An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
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Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

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In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...
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Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

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Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...
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One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

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This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
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Stratified Sampling Method01:16

Stratified Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
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相关实验视频

Updated: May 30, 2025

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
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Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

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集群序列数据与混合马尔科夫链与共变量使用多个简单的受约束优化程序 (MSiCOR).

Priyam Das1, Deborshee Sen2, Debsurya De3

  • 1Department of Biostatistics, Virginia Commonwealth University, Richmond, VA.

Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America
|January 29, 2025
PubMed
概括
此摘要是机器生成的。

一种新的全局优化方法提高了混合马尔科夫模型 (MMM) 对聚类事件序列的性能,超过了预期最大化 (EM) 算法. 该技术用于根据治疗数据识别多发性硬化症 (MS) 患者的子组.

关键词:
改变疾病的疗法.全球优化全球优化马尔科夫连锁是什么意思医疗序列数据数据 医学序列数据混合模型的混合模型.多发性硬化症是多发性硬化症.

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Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
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Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
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相关实验视频

Last Updated: May 30, 2025

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
09:17

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

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Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
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Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
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科学领域:

  • 计算统计学 计算统计学
  • 机器学习 机器学习
  • 生物统计学 生物统计学

背景情况:

  • 混合马尔科夫模型 (MMM) 对聚类事件序列有价值,但由于多模式性,在概率最大化方面面临挑战.
  • 通常用于MMM参数估计的预期-最大化 (EM) 算法不能保证趋同.
  • 在受约束的参数空间上最大化MMM概率带来了显著的计算困难.

研究的目的:

  • 开发一种强大的全球优化技术,以最大限度地提高混合马尔科夫模型的可能性.
  • 为了提高混合马尔科夫模型在聚类复杂事件序列的性能.
  • 根据疾病修饰疗法 (DMT) 序列和临床共变量,将改进的MMM应用于聚类多发性硬化症 (MS) 患者.

主要方法:

  • 开发了一种基于模式搜索的全局优化技术,能够优化对象函数的简单集合.
  • 使用这种技术来最大限度地提高混合马尔科夫模型的概率函数.
  • 利用DMT处方数据和相关的临床特征 (共变量) 应用增强型MMM对MS患者进行集群.

主要成果:

  • 提出的基于模式搜索的全球优化方法,与现有的全球优化技术相比,表现优越.
  • 在模拟实验中,新方法在混合马尔科夫模型估计中超过了预期最大化 (EM) 算法.
  • 对多发性硬化症患者进行集群研究,发现基于DMT序列和共变体的三个不同的子组,在各个集群中发现了显著差异.

结论:

  • 基于模式搜索的新型全球优化技术有效地解决了混合马尔科夫模型概率最大化的挑战.
  • 与传统的EM算法相比,这种方法为MMM参数估计提供了更好的准确性和可靠性.
  • 对多发性硬化患者数据的应用成功确定了临床相关的子组,为个性化治疗策略铺平了道路.