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

Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

5.9K
Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
5.9K
mTOR Signaling and Cancer Progression03:03

mTOR Signaling and Cancer Progression

4.6K
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...
4.6K
PI3K/mTOR/AKT Signaling Pathway01:22

PI3K/mTOR/AKT Signaling Pathway

5.3K
The mammalian target of rapamycin  (mTOR) is a serine/threonine kinase that regulates growth, proliferation, and cell survival in response to hormones, growth factors, or nutrient availability. This kinase exists in two structurally and functionally distinct forms: mTOR complex 1  (mTORC1) and mTOR complex 2  (mTORC2). The first form (mTORC1) is composed of a rapamycin-sensitive Raptor and proline-rich Akt substrate, PRAS40. In contrast,  mTORC2 consists of a...
5.3K
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

6.9K
Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
6.9K
Targeted Cancer Therapies02:57

Targeted Cancer Therapies

8.6K
The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against...
8.6K
MAPK Signaling Cascades01:07

MAPK Signaling Cascades

7.8K
Mitogen-activated protein kinase, or MAPK pathway, activates three sequential kinases to regulate cellular responses such as proliferation, differentiation, survival, and apoptosis. The canonical MAPK pathway starts with a mitogen or growth factor binding to an RTK. The activated RTKs stimulate Ras, which recruits Raf or MAP3 Kinase (MAPKKK), the first kinase of the MAPK signaling cascade. Raf further phosphorylates and activates MEK or MAP2 Kinases (MAPKK), which in turn phosphorylates MAP...
7.8K

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

Deep learning reveals antimicrobial peptides within prions.

Nature microbiology·2026
Same author

Enzyme-Regulated Non-Thermal Fluctuations Enhance Ligand Diffusion and Receptor-Mediated Endocytosis.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

A generative artificial intelligence approach for peptide antibiotic optimization.

Nature machine intelligence·2026
Same author

MYC and AP-1 oncogenes cooperatively bind enhancers to rewire transcription.

NAR cancer·2026
Same author

Modeling tumor transport and growth with poroelastic biopolymer networks.

Soft matter·2026
Same author

pH-Tunable, Ligand-Free Selective Separation of Rare Earth Elements Using Silica Nanoparticles.

ACS applied materials & interfaces·2026

相关实验视频

Updated: Jan 10, 2026

A Method for Screening and Validation of Resistant Mutations Against Kinase Inhibitors
12:40

A Method for Screening and Validation of Resistant Mutations Against Kinase Inhibitors

Published on: December 7, 2014

15.2K

整合性机器学习预测了用于精确瘤学的激酶突变的激活.

Yiming Wang, Fangping Wan, Zhangtao Chen

    bioRxiv : the preprint server for biology
    |November 24, 2025
    PubMed
    概括

    基诺姆-AI是一种新的机器学习工具,可以预测基因突变激酶是否会激活它们. 这有助于通过识别针对性治疗的关键突变来个性化癌症治疗.

    科学领域:

    • 生物化学和分子生物学
    • 计算生物学和生物信息学
    • 基因组学和遗传学 基因组学和遗传学

    背景情况:

    • 蛋白激酶是调节细胞过程的重要酶;突变的异常激活驱动癌症的进展.
    • 了解酶误解突变对于个性化癌症治疗和预测药物疗效至关重要.
    • 目前的方法很难准确预测酶突变的功能影响.

    研究的目的:

    • 开发一个精确的机器学习框架,Kinome-AI,用于将激酶误传突变分类为激活或非激活.
    • 整合多模式数据,包括序列和结构特征,以提高预测能力.
    • 为了能够精确地识别致癌的激酶突变,用于有针对性的治疗策略.

    主要方法:

    • 开发了Kinome-AI,这是一个集成式机器学习框架,利用多模式功能.
    • 结合了残留水平的生物化学变化,蛋白质语言模型序列嵌入和分子建模结构描述器.
    • 采用教师-学生学习策略来归因缺失的结构数据,利用可用的结构信息.

    主要成果:

    • 在110个激酶中,Kinome-AI在1003个突变中实现了0.85的AUROC和0.76的BACC.
    • 该模型显著优于现有的生物信息学和通用变异效应预测器.
    • 归算策略提高了性能,而不需要对新突变进行结构输入.

    更多相关视频

    Kinase Inhibitor Screening In Self-assembled Human Protein Microarrays
    13:22

    Kinase Inhibitor Screening In Self-assembled Human Protein Microarrays

    Published on: October 23, 2019

    8.2K
    Assessment of Resistance to Tyrosine Kinase Inhibitors by an Interrogation of Signal Transduction Pathways by Antibody Arrays
    07:42

    Assessment of Resistance to Tyrosine Kinase Inhibitors by an Interrogation of Signal Transduction Pathways by Antibody Arrays

    Published on: September 19, 2018

    8.3K

    相关实验视频

    Last Updated: Jan 10, 2026

    A Method for Screening and Validation of Resistant Mutations Against Kinase Inhibitors
    12:40

    A Method for Screening and Validation of Resistant Mutations Against Kinase Inhibitors

    Published on: December 7, 2014

    15.2K
    Kinase Inhibitor Screening In Self-assembled Human Protein Microarrays
    13:22

    Kinase Inhibitor Screening In Self-assembled Human Protein Microarrays

    Published on: October 23, 2019

    8.2K
    Assessment of Resistance to Tyrosine Kinase Inhibitors by an Interrogation of Signal Transduction Pathways by Antibody Arrays
    07:42

    Assessment of Resistance to Tyrosine Kinase Inhibitors by an Interrogation of Signal Transduction Pathways by Antibody Arrays

    Published on: September 19, 2018

    8.3K

    结论:

    • 基诺姆-AI提供了一种可靠的方法来预测基因酶突变激活状态.
    • 这个框架量化了与癌症相关的激酶突变中的序列结构功能关系.
    • 通过告知有针对性的治疗决策,Kinome-AI有望推进个性化癌症治疗.