相关实验视频
Updated: Jun 6, 2025

07:46
Setting Limits on Supersymmetry Using Simplified Models
Published on: November 15, 2013
8.5K
关于前期采样计划密度的近乎紧密的下界
Bryce Kille1, Ragnar Groot Koerkamp2, Drake McAdams1
1Department of Computer Science, Rice University, Houston, TX, USA.
bioRxiv : the preprint server for biology
|November 28, 2024
概括
新的研究确定了k-mer采样方案的近乎紧密的下界,显著提高了序列分析的效率. 这一发现表明,目前的方法比以前理解的更接近最佳密度.
科学领域:
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
- 序列分析 序列分析
背景情况:
- 采样k-mers对于序列分析算法至关重要.
- 最小化方案保证每个窗口至少选择一个k-mer,但为了效率,寻求低密度方案.
研究的目的:
- 为了在前期抽样方案的密度上建立一个近乎紧密的下界,将最小化方案概括为.
- 评估理论下限和实际k-mer采样方案密度之间的差距.
主要方法:
- 证明前期抽样计划的理论下限.
- 分析各种参数范围 (小/大k和w) 的边界密度.
- 将边界与现有方案进行比较,例如基于双循环集合的最小化器和mod-minimizer.
主要成果:
- 在前期采样方案密度上,一个近乎紧密的下界被证明.
- 当k对小参数与0modw一致时,边界是紧的.
- 对于较大的参数,边界近似值为O (k/w).
- 现有的方案被证明比以前认为的更接近最佳密度.
结论:
- 新的下界重新评估了当前k-mer采样方案的性能.
- 对于minimap2的HiFi设置 (k=25,w=32),最知名的方案仅比最佳设置密度高3%.
- 当k与0mod w一致,字母表大小接近无限时,mod-minimizer可以实现最佳密度.
相关概念视频
Sampling Theorem
302
In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
302
Sampling Plans
167
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...
167
Sampling Distribution
12.3K
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...
12.3K
Upsampling
204
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
204
Downsampling
130
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
130
Convenience Sampling Method
8.6K
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.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
8.6K

