Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Cancers Originate from Somatic Mutations in a Single Cell02:21

Cancers Originate from Somatic Mutations in a Single Cell

11.8K
Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
11.8K
Cancer-Critical Genes I: Proto-oncogenes01:33

Cancer-Critical Genes I: Proto-oncogenes

8.7K
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...
8.7K
Mutagenicity and Carcinogenicity01:25

Mutagenicity and Carcinogenicity

1.2K
Mutagenicity and carcinogenicity refer to the ability of drugs to cause genetic defects and induce cancer, respectively. The International Agency for Research on Cancer (IARC) classifies agents into four groups based on their carcinogenic potential. Group 1 agents are known human carcinogens; group 2A agents are probably carcinogenic to humans; group 3 agents lack data to support their role in carcinogenesis; and group 4 includes agents for which data support that they are not likely to be...
1.2K
mTOR Signaling and Cancer Progression03:03

mTOR Signaling and Cancer Progression

3.8K
The mammalian target of rapamycin or mTOR protein was discovered in 1994 due to its direct interaction with rapamycin. The protein gets its name from a yeast homolog called TOR. The mTOR protein complex in mammalian cells plays a major role in balancing anabolic processes such as the synthesis of proteins, lipids, and nucleotides and catabolic processes, such as autophagy in response to environmental cues, such as availability of nutrients and growth factors.
The mTOR pathway or the...
3.8K
Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

6.2K
Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
6.2K
Cancer-Critical Genes II: Tumor Suppressor Genes01:05

Cancer-Critical Genes II: Tumor Suppressor Genes

7.3K
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...
7.3K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Clinical outcomes, patterns of relapse and molecular landscape of advanced stage High Grade B-cell Lymphoma.

Blood advances·2026
Same author

SOAT1 expression associates with prognosis, immune environment and biochemical indicators in glioma.

Discover oncology·2026
Same author

Enhanced phosphorus availability and uptake in Salvia miltiorrhiza associated with humic-induced changes in soil phosphorus fractions.

Scientific reports·2026
Same author

Risk of malignancy for biliary cytology based on World Health Organization (WHO) reporting system for pancreaticobiliary cytopathology.

Cancer cytopathology·2026
Same author

[Mechanism on synergistic analgesia and intestinal motility antagonism of electroacupuncture combined with morphine].

Zhongguo zhen jiu = Chinese acupuncture & moxibustion·2026
Same author

Vitexin inhibits renal cell carcinoma progression by targeting Galectin-1-mediated glycolytic metabolism.

Molecular biology reports·2026

相关实验视频

Updated: Jun 13, 2025

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
06:52

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres

Published on: July 22, 2020

6.5K

贝叶斯的方法通过相互排他性来识别癌症途径内的驱动突变.

Xinjun Wang, Caroline Kostrzewa, Allison Reiner

    bioRxiv : the preprint server for biology
    |June 12, 2025
    PubMed
    概括

    识别癌症驱动突变是一个挑战. 贝叶斯MAGPIE通过分析突变类型和基因驱动频率来提高准确性,增强癌症基因组学发现.

    科学领域:

    • 癌症基因组学 癌症基因组学
    • 计算生物学 计算生物学
    • 统计遗传学 统计遗传学

    背景情况:

    • 从乘客突变区分驾驶员突变是癌症基因组学的一个关键挑战.
    • 计算方法对于分析大型基因组数据集和识别新型驱动程序候选人至关重要.
    • 相互排他性分析是一个有吸引力的框架,用于识别参与癌症途径的基因.

    研究的目的:

    • 引入贝叶斯MAGPIE,一种用于识别癌症驱动基因的增强统计方法.
    • 通过结合突变类型信息和建模基因特异性驱动频率来提高驱动突变识别的准确性.
    • 为分析癌症基因组数据提供强大的计算工具.

    主要方法:

    • 贝叶斯MAGPIE使用贝叶斯层次模型框架来改进MAGPIE方法.
    • 该方法结合了突变类型信息,以区分基因内的变异的功能影响.
    • 使用Dirichlet priori来建模基因特定的驱动频率,控制推断的驱动器集的稀疏性.

    主要成果:

    • 进行了广泛的模拟研究,以评估BayesMAGPIE的估计偏差和准确性.
    • 用八种癌症类型的TCGA数据对原始MAGPIE方法进行了基准测试.
    • 改进的方法在识别驱动基因方面表现出更高的准确性.

    更多相关视频

    A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis
    07:41

    A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis

    Published on: March 8, 2022

    2.4K
    Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
    07:15

    Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

    Published on: January 16, 2019

    11.0K

    相关实验视频

    Last Updated: Jun 13, 2025

    Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
    06:52

    Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres

    Published on: July 22, 2020

    6.5K
    A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis
    07:41

    A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis

    Published on: March 8, 2022

    2.4K
    Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
    07:15

    Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

    Published on: January 16, 2019

    11.0K

    结论:

    • 贝叶斯MAGPIE提供了一种更准确的方法,通过利用突变类型和频率信息来识别癌症驱动突变.
    • 该方法与大多数癌症中稀疏的驱动基因组的生物学预期一致.
    • 贝叶斯MAGPIE代表了癌症基因组学研究计算工具的重大进步.