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相关概念视频

Propagation of Uncertainty from Random Error00:59

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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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Survival Tree01:19

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Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
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Translesion DNA Polymerases02:10

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Translesion (TLS) polymerases rescue stalled DNA polymerases at sites of damaged bases by replacing the replicative polymerase and installing a nucleotide across the damaged site. Doing so, TLS allows additional time for the cell to repair the damage before resuming regular DNA replication.
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In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
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The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
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DNA replication is a well-evolved process that copies millions of base pairs with high fidelity during each cell division. Occasionally a wrong base or a long stretch of wrong bases may get added to the daughter strands. If the errors are left unchecked, cells might accumulate several mutations that might endanger their  survival. Therefore, the copying errors are checked and repaired at three levels.
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在新的重复-分歧模型中模拟弱攻击与节点损失.

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  • 1Department of Statistics, University of Oxford, 24-29 St. Giles', Oxford OX1 3LB, UK.

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概括
此摘要是机器生成的。

这项研究引入了一种新的重复-分歧模型,用于蛋白质-蛋白质相互作用网络,包括基因丢失. 改进后的模型更好地反映了现实世界的网络结构及其对攻击的反应.

关键词:
重复差异模型的重复差异模型基因损失是基因的损失.蛋白蛋白相互作用网络 蛋白蛋白相互作用网络弱势的攻击是弱势的攻击.

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科学领域:

  • 计算生物学 计算生物学
  • 网络科学 网络科学
  • 系统生物学 系统生物学

背景情况:

  • 蛋白与蛋白相互作用 (PPI) 网络对于理解生物过程和药物开发至关重要.
  • 现有的重复-分歧模型无法准确地表示真正的PPI网络属性,经常产生过于稀疏或过于密集的网络.
  • 目前的模型没有考虑基因丢失,这是生物网络进化的重要因素.

研究的目的:

  • 为PPI网络引入一种新的重复-分歧模型,该模型包含节点损失.
  • 分析新模型产生的网络的结构性质.
  • 评估模型在攻击场景下复制真实PPI网络行为的能力.

主要方法:

  • 开发了一个新的重复-分歧模型,包含一个节点损失机制.
  • 在模型生成网络和真实PPI网络 (大肠杆菌,细菌) 上应用强弱攻击策略.
  • 将攻击对模型网络的影响与实际生物网络进行了比较.

主要成果:

  • 新模型生成的网络中,孤立蛋白质的比例严格在0和1之间,弥合了稀疏和密集模型之间的差距.
  • 由节点损失模型生成的网络表现出更现实的属性.
  • 该模型对强弱攻击的反应更接近于真实PPI网络的反应.

结论:

  • 拟议的重复-分歧模型与节点损失提供了更准确的生物PPI网络的表示.
  • 这种改进的模型可以增强进化洞察力,并有助于药物开发战略.
  • 该模型在模拟网络抵御攻击方面的忠实性验证了其在系统生物学研究中的实用性.