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相关概念视频

Correlations02:20

Correlations

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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Correlation and Causation01:27

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Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
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Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Correlation01:09

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In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
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Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
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Nearly all the energy used by cells comes from the bonds that make up complex organic compounds. These organic compounds are broken down into simpler molecules, such as glucose. As a result, cells extract energy from glucose over many chemical reactions—a process called cellular respiration.
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软组织瘤中的转录组子组与形态亚型,基因组特征和结果相关.

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概括

转录组测序 (RNA-seq) 改善软组织瘤 (STT) 的分类,并识别新的基因融合. 这种分子方法揭示了预后子组,有助于诊断和预测这些不同癌症的患者结果.

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科学领域:

  • 在瘤学瘤学.
  • 基因组学就是基因组学.
  • 分子病理学分子病理学

背景情况:

  • 软组织瘤 (STT) 是一组多样化的100多种瘤.
  • 许多性传播疾病亚型缺乏可靠的诊断或预后标记,突出显示了需要先进的分类方法.

研究的目的:

  • 评估转录组测序 (RNA-seq) 对分类STT的临床实用性.
  • 使用RNA-seq数据在STT中识别出具有预后意义的子组.

主要方法:

  • 进行了RNA测序 (RNA-seq),对704种瘤进行了56种组织学亚型的测序.
  • 全球基因表达 (GGE) 资料,融合转录,基因组特征和临床病理学数据的综合分析.
  • 使用无监督集群和机器学习来完善分类并发现预后签名.

主要成果:

  • 确定了200多种致病基因融合,其中包括40种新型基因融合.
  • 对于许多亚型,特别是具有特定基因融合的亚型,观察到明显的GGE概况.
  • 在5.7%的病例中发生了诊断性重新分类;转录组子集群与复杂的肉瘤中无转移生存相关.

结论:

  • 转录基因分析提升了诊断的准确性,并揭示了STT的新型瘤性融合.
  • RNA-seq为软组织瘤提供了有价值的预后信息.
  • 建议进行多中心研究,以充分利用由于STT多样性的RNA-seq潜力.