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相关概念视频

Review and Preview01:10

Review and Preview

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In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...
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Review and Preview01:13

Review and Preview

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Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
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Random and Systematic Errors01:20

Random and Systematic Errors

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Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
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Systematic Sampling Method01:17

Systematic 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.
Systematic sampling is one of the simplest methods...
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Propagation of Uncertainty from Systematic Error01:10

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The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
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Computed Tomography

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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相关实验视频

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有机体的基于细胞的计算模型:系统性审查.

Monica Neagu1,2, Andreea Robu3, Stelian Arjoca1,2

  • 1Department of Functional Sciences, "Victor Babeș" University of Medicine and Pharmacy of Timisoara, E. Murgu Sq., No. 2, 300041 Timisoara, Romania.

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计算器官模型为器官发育和疾病建模提供了洞察力. 本系统性审查分析了in silico模型,揭示了它们在指导实验工作和加深对有机生物学的理解方面的力量.

关键词:
基于代理的模型基于代理的模型.在模型模型中.有机体生长的成长有机体生长.

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科学领域:

  • 生物技术是生物技术.
  • 计算生物学 计算生物学
  • 发育生物学 发展生物学

背景情况:

  • 器官体是体外自我组织的多细胞结构,模仿器官的结构和功能.
  • 机器人技术使发展和疾病的新型建模成为可能,但也面临着挑战.
  • 计算模型对于理解有机体生长和优化培养至关重要.

研究的目的:

  • 在单细胞或亚细胞分辨率下系统地审查in silico有机体模型.
  • 分析从计算器官模拟中获得的洞察力.
  • 为了确定下一代计算器官模型的趋势.

主要方法:

  • 在PubMed,Scopus和Web of Science的系统文献搜索.
  • 选了439个记录,其中32篇论文符合纳入标准.
  • 根据有机体类型 (肠道,呼吸道,胰腺,神经,脏,瘤等) 确定模型的分类. ) 的情况.

主要成果:

  • 计算机模拟有效指导实验性有机体研究.
  • 节的模型阐明了各种各样的有机体行为 (例如,呼吸道旋转,胰腺振荡,神经模式,脏新生).
  • 结合了in silico和in vitro的研究,获得了对有机体形态发生的深刻理解.

结论:

  • 计算器官模型是实验指导和生物洞察的宝贵工具.
  • 未来的模型很可能将详细的干细胞调节电路和机器学习与高通量成像相结合.
  • 在 silico 方法显著提升了有机体研究领域.