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相关概念视频

Conformity01:20

Conformity

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Conformity is the change in a person’s behavior to go along with the group, even if that person does not agree with the group.
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Histone variants are the histone proteins with structural and sequence variations. These variants may be regarded as “mutant” forms that replace their canonical histone counterparts in the nucleosomes. Specific post-translational modifications on the histone variants enable further chromatin complexity and regulate tissue-specific gene expression. The most common histone variants are from histone H2A, H2B, and linker histone H1 families. However, several variants of histone H3...
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Unlike ethane and propane that have only two major conformations, butane has more than two conformers. The staggered form of butane in which the bulky methyl groups on the two carbons are placed on opposite sides, that is, at a dihedral angle of 180°, is the lowest energy, most stable form — called the anti conformer. This conformation is stabilized due to the absence of steric repulsion between the largely spaced out methyl groups. The other two staggered conformations are...
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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
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Interpreting R Charts01:22

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R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
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Conformations of Cycloalkanes02:29

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Adolf von Baeyer attempted to explain the instabilities of small and large cycloalkane rings using the concept of angle strain — the strain caused by the deviation of bond angles from the ideal 109.5° tetrahedral value for sp3  hybridized carbons. However, while cyclopropane and cyclobutane are strained, as expected from their highly compressed bond angles, cyclopentane is more strained than predicted, and cyclohexane is virtually strain-free. Hence, Baeyer’s theory that...
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相关实验视频

Updated: Jan 29, 2026

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
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Published on: September 19, 2025

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DyVarMap:整合合规动力学和可解释的机器学习,用于FGFR2中的癌症相关误解变异分类.

Yiyang Lian1, Amarda Shehu1,2

  • 1School of Systems Biology, George Mason University, Manassas, VA 20110, USA.

Bioengineering (Basel, Switzerland)
|January 28, 2026
PubMed
概括
此摘要是机器生成的。

在癌症中解释基因变异是具有挑战性的. 一个新的框架DyVarMap使用结构动态来预测变异效应,为精确瘤学提供机械洞察力.

关键词:
在AlphaFold2中,我们将使用AlphaFold2.在FGFR2中.构造动力学 构造动力学机器学习是机器学习.错误的意义的变体精确瘤学 精确瘤学受体氨酸激酶的受体.变体效应预测变体效应预测

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科学领域:

  • 计算生物学是一种计算生物学.
  • 结构生物信息学 结构生物信息学
  • 精确瘤学是一门精确的专业.

背景情况:

  • 解释癌症基因中的误解变异是困难的,许多被归类为不确定的意义 (VUS) 的变异.
  • 像FGFR2这样的受体氨酸激酶的功能取决于结构动力学,使变异分析复杂化.
  • 现有的基于序列的预测器往往缺乏对变异效应的机制解释.

研究的目的:

  • 开发DyVarMap,一个可解释的结构学习框架,用于预测癌症相关基因变异的致病性.
  • 整合形态动力学到变量效应预测中,以提高准确性和机理性理解.
  • 提供可测试的假设,用于精密瘤学的实验验证.

主要方法:

  • DyVarMap集成了基于AlphaFold2的集合生成与物理驱动的精细化和多重学习.
  • 监督分类模型使用了五个生物物理动机的几何特征.
  • SHAP分析为变异性病原性预测提供了机制性归因.

主要成果:

  • DyVarMap成功地对FGFR2变异的病原性进行了分类,产生了多样化的形状组合,并确定了转移稳定的状态.
  • 与PolyPhen-2和AlphaMissense相比,对十种酶域变体的外部验证实现了0.77的AUROC,校准优越.
  • 特性重要性分析强调了K659-E565盐桥距离和DFG图案二面角作为关键预测因素,将预测与已知的激活机制联系起来.

结论:

  • DyVarMap有效地弥合了静态结构预测和动态意识的功能评估之间的差距.
  • 该框架为变异效应提供了结构连贯的机制解释,有助于精确瘤学.
  • 将结构动力学纳入变异效应预测中,为临床应用和实验验证提供了重要的价值.