相关实验视频
Updated: Jun 2, 2025

10:36
Rare Event Detection Using Error-corrected DNA and RNA Sequencing
Published on: August 3, 2018
12.0K
WeTICA:以定向搜索加权集团为基础的增强采样方法,用于估计在缩小维空间中的罕见事件动力学
Sudipta Mitra1, Ranjit Biswas1, Suman Chakrabarty1
1Department of Chemical and Biological Sciences, S. N. Bose National Centre for Basic Sciences, Block-JD, Sector-III, Salt Lake, Kolkata 700106, India.
The Journal of chemical physics
|January 15, 2025
概括
我们开发了一种新的无容器加权合集 (WE) 模拟方法WeTICA,以高效地估计罕见事件动力学. 这种方法精确计算了蛋白质展开时间,与传统方法相比,模拟工作量大大减少.
科学领域:
- 计算化学计算化学
- 生物物理学的生物物理.
- 分子动力学模拟模型
背景情况:
- 从分子动力学模拟中估计罕见事件动力学是具有挑战性的.
- 增强的采样方法,如权重组合 (WE) 模拟,提高效率,但往往依赖于复杂的分类策略.
- 在WE模拟中优化集体变量 (CV) 空间分区可能很困难.
研究的目的:
- 引入一个新的"无桶"权重合奏 (WE) 模拟算法,命名为WeTICA.
- 为了绕过在WE模拟中优化分类程序的需求.
- 使用一种新的方法,准确估计罕见事件动力学,特别是蛋白质展开时间.
主要方法:
- 开发了一个无垃圾WE模拟协议 (WeTICA).
- 利用一个低维的集体变量 (CV) 空间来指导WE模拟.
- 采用时间滞后的独立组件分析 (TICA) 固有向量作为蛋白质展开的CV.
- 引入了重新采样的新步行者选择标准.
主要成果:
- 成功恢复了三种蛋白质的展开动力学 (TC5b Trp子突变,TC10b Trp子突变,蛋白质G).
- 在计算的展开时间 (340μs) 中获得了良好的准确性.
- 与传统方法相比,累计WE模拟时间减少了一次数量级.
- 展示了算法的适用性与TICA以外的线性CV.
结论:
- WeTICA算法提供了一种高效准确的方法来估计罕见事件动力学.
- 这种无 bin 方法通过消除 bin 优化需求来简化 WE 模拟.
- 开发的步行者选择标准为非线性CV空间提供了进一步改进的潜力.
相关概念视频
Mechanistic Models: Compartment Models in Individual and Population Analysis
26
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
26
Sampling Plans
165
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...
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...
165
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
39
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
39
Protein Dynamics in Living Cells
2.1K
Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...
2.1K
Censoring Survival Data
62
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
62
Random Sampling Method
11.0K
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...
11.0K

