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相关概念视频

Aggregates Classification01:29

Aggregates Classification

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Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
327
Types of Aggregate Grading01:15

Types of Aggregate Grading

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Aggregate grading is crucial in economically obtaining a concrete mix with adequate strength, reasonable workability, and minimal segregation. There are four types of aggregate gradation: well-graded, uniformly (or one-sized) graded, gap-graded, and open-graded.
Well-graded aggregates include a complete range of necessary size fractions that fit together to create a dense matrix with minimal voids, represented by a smooth, continuous gradation curve. This type of grading ensures good...
527
Mass Analyzers: Common Types01:19

Mass Analyzers: Common Types

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The quadrupole mass analyzer consists of four cylindrical metal rods arranged in a diamond carrying a DC voltage and a radio-frequency AC voltage. The motion of ions through the quadrupole depends on the field strength, causing only ions of a certain m/z to resonate successfully and strike the detector at a given field strength. Though the transmission rate for these analyzers is high, the exact elemental composition of the sample is not determined because of low resolution; however, they are...
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Data Collection by Observations01:08

Data Collection by Observations

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Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
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Cluster Sampling Method01:20

Cluster Sampling Method

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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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How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

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A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
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塔达:对分类学有意识的数据集聚合器.

Emil Hägglund1, Siv G E Andersson1, Lionel Guy2

  • 1Molecular Evolution, Department of Cell and Molecular Biology, Science for Life Laboratory, Biomedical Centre, Uppsala University, SE-751 24 Uppsala, Sweden.

Bioinformatics (Oxford, England)
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概括
此摘要是机器生成的。

选择代表性基因组用于细菌和考古物种遗传学分析至关重要. TADA (分类学意识数据集选择) 是一个新的工作流程,可以自动化这一过程,确保基因组数据集的质量和多样性.

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科学领域:

  • 基因组学就是基因组学.
  • 生物信息学是一种生物信息学.
  • 进化生物学 进化生物学

背景情况:

  • 越来越多的细菌和古人类基因组的测序使得先进的遗传学和比较基因组研究成为可能.
  • 然而,利用所有可用的基因组数据进行遗传遗传重建是计算上具有挑战性的,并且可以引入因多样性分布不均的偏差而导致的偏差.

研究的目的:

  • 开发一种用户友好的软件解决方案,以高效,可靠地对 prokaryotic 基因组进行子样本采集,以进行基因组学分析.
  • 在大规模基因组研究中解决对自动分类学意识数据集选择的需求.

主要方法:

  • 实现TADA作为一个Snakemake工作流程.
  • 开发一种具有分类学意识的数据集选择过程,具有可调节的细分度.
  • 包括基因组质量控制和分支平衡参数.

主要成果:

  • 塔达有助于从各种 prokaryotic 血统中选择具有代表性的基因组子集.
  • 工作流允许用户定义的样本采集策略跨 prokaryotic 多样性.
  • 对基因组质量和家族遗传平衡的限制被整合到选择过程中.

结论:

  • 塔达为构建高质量,多样化的基因组数据集以进行遗传学推断提供了一种实用解决方案.
  • 这种工具提高了对 Prokaryotes 进行大规模植物遗传分析的可行性.
  • 自动化,分类学意识的亚抽样提高了比较基因组学的效率和准确性.