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相关概念视频

lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

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In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
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Cancer-Critical Genes I: Proto-oncogenes01:33

Cancer-Critical Genes I: Proto-oncogenes

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Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
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Cancer-Critical Genes II: Tumor Suppressor Genes01:05

Cancer-Critical Genes II: Tumor Suppressor Genes

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Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
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Induced Pluripotent Stem Cells01:06

Induced Pluripotent Stem Cells

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Stem cells are undifferentiated cells that divide and produce different cell types. Ordinarily, cells that have differentiated into a specific cell type are terminally differentiated; however, scientists have found a way to reprogram these mature cells so that they dedifferentiate and return to an unspecialized, proliferative state. These cells are pluripotent like embryonic stem cells—able to produce all cell types—and are called induced pluripotent stem cells (iPSCs).
Somatic...
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相关实验视频

Updated: May 10, 2025

Author Spotlight: FISH as a Tool for Precise Gene Amplification Assessment in Cancer Specimens
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Author Spotlight: FISH as a Tool for Precise Gene Amplification Assessment in Cancer Specimens

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使用人工智能照明癌症的非编码基因组.

Maria Del Mar Alvarez-Torres1, Xi Fu1, Raul Rabadan2

  • 1Columbia University Medical Center, New York, United States.

Cancer research
|April 22, 2025
PubMed
概括

人工智能 (AI) 通过分析非编码突变来推进癌症基因组研究. 本综述比较了用于识别功能变异和预测癌症基因表达影响的AI模型.

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.
  • 癌症研究 癌症研究

背景情况:

  • 非编码癌症基因组庞大而复杂,需要先进的分析策略.
  • 人工智能 (AI) 为了解癌症中的基因组调节提供了强大的工具.
  • 非编码突变在癌症发育中起着重要作用,但往往不太了解.

研究的目的:

  • 审查用于分析非编码癌症基因组的关键AI模型.
  • 为了比较AI方法来识别功能性非编码变体并预测它们对基因表达的影响.
  • 为将AI整合到癌症基因组学研究中的研究人员提供实用见解.

主要方法:

  • 对过去十年开发的AI模型进行非编码变体分析的审查.
  • 专注于识别功能非编码变体和预测基因表达影响的模型.
  • 对模型目标,数据要求,特征和结果的分析.

主要成果:

  • 人工智能模型越来越有效地识别癌症中的功能非编码突变.
  • 这些模型可以预测非编码变异对基因表达的影响.
  • 十年的AI开发已经为癌症基因组学带来了各种各样的工具.

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Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence
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Author Spotlight: FISH as a Tool for Precise Gene Amplification Assessment in Cancer Specimens

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结论:

  • 人工智能正在彻底改变对非编码癌症基因组的分析.
  • 了解非编码突变对于推进癌症研究和治疗至关重要.
  • 研究人员可以利用人工智能工具来增强他们对癌症基因组学的研究,无论他们的计算背景如何.