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相关概念视频

Random Sampling Method01:09

Random 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. Data are the result of sampling from a 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. Among the various sampling methods used by...
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State Space Representation01:27

State Space Representation

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The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
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Sampling Methods: Overview01:06

Sampling Methods: Overview

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A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
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Sampling Plans01:23

Sampling Plans

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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
181
Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

218
Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
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Sampling Distribution01:12

Sampling Distribution

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Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
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Updated: Jun 29, 2025

Author Spotlight: Advancing Alzheimer's Research &#8211; Exploring Early Detection and Multi-Omics Approaches
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通过变化自编码器的蛋白质组合生成 隐藏空间采样 隐藏空间采样

Sanaa Mansoor1,2,3, Minkyung Baek1,2,4, Hahnbeom Park1,2,5

  • 1Department of Biochemistry, University of Washington, Seattle, Washington 98195, United States.

Journal of chemical theory and computation
|March 28, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种使用变异自编码器 (VAE) 产生多样化的蛋白质结构的新方法,这对于药物发现至关重要. 该方法准确地模拟了蛋白质构造,优于K-Ras蛋白质结构预测的现有方法.

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科学领域:

  • 计算生物学 计算生物学
  • 结构生物学 结构生物学
  • 药物发现 药物发现 药物发现

背景情况:

  • 绘制蛋白质构造组合的映射对于理解功能和开发向治疗来说至关重要.
  • 高维的蛋白质结构数据对计算建模和组合生成提出了重大挑战.

研究的目的:

  • 开发和验证一种使用变异自编码器 (VAE) 生成蛋白质结构组合的新方法.
  • 评估基于VAE的方法在准确采样蛋白质构造方面的能力,这与药物发现有关,特别是对于K-Ras蛋白.

主要方法:

  • 使用变异自编码器 (VAE) 来减少蛋白质结构数据的维度,创建连续的低维表示.
  • 采用结构质量指标来指导在VAE潜伏空间中的搜索.
  • 使用RoseTTAFold生成3D蛋白质结构,由从潜空间采集的样本信息提供信息.
  • 在K-Ras晶体结构和分子动力学 (MD) 模拟快照上训练了VAE,评估了与保留的晶体结构相比的性能.

主要成果:

  • 基于VAE的潜空间采样快速生成具有高结构质量的蛋白质组合.
  • 该方法在1 Å内获得了持久的K-Ras晶体结构的采样,与MD模拟和AlphaFold2.2相比,显示出更高的一致性.
  • 生成的组合成功地重复了K-Ras结构中的神秘口袋,从而实现了有效的小分子对接.

结论:

  • 开发的以VAE驱动的方法提供了一种高效和准确的方法来生成蛋白质构造组合.
  • 这种技术显著提升了为药物标识和小分子抑制剂的设计建模蛋白质结构的能力.
  • 改进的采样一致性和口袋回顾对加速药物发现管道充满希望.