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相关概念视频

Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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A living cell's primary tasks of obtaining, transforming, and using energy to do work may seem simple. However, the second law of thermodynamics explains why these tasks are harder than they appear. None of the energy transfers in the universe are completely efficient. In every energy transfer, some amount of energy is lost in a form that is unusable. In most cases, this form is heat energy. Thermodynamically, heat energy is defined as the energy transferred from one system to another that...
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A gene is the fundamental unit of heredity. Every individual has two copies of each gene, one inherited from each parent. Although most people contain the same genes, there is a small fraction that is slightly different amongst people. A gene with a small difference in its sequence of DNA bases forms different alleles, contributing to different phenotypes.
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Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.
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Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
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对于基因表达模式的最大模型.

Camilla Sarra1, Leopoldo Sarra2, Luca Di Carlo1,3

  • 1Princeton University, Joseph Henry Laboratories of Physics, Princeton, New Jersey 08544, USA.

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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概率方法,使用最大来分析单细胞基因表达数据. 它揭示了基于哺乳动物大脑中mRNA表达模式的新兴细胞类型和亚型.

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科学领域:

  • 计算生物学 计算生物学
  • 基因组学就是基因组学.
  • 统计物理 统计物理

背景情况:

  • 高通量单细胞实验产生了大量的基因表达数据.
  • 目前的分析方法往往假定了预定义的细胞类型,限制了发现.
  • 了解细胞类型的异质性在生物学中至关重要.

研究的目的:

  • 开发一种新的,无假设的方法来分析单细胞基因表达数据.
  • 从复杂的表达模式中识别新出现的细胞类型和亚型.
  • 为了解细胞状态分布提供一个概率框架.

主要方法:

  • 在概率模型中应用最大的原理.
  • 使用实验手段和相关性构建和验证一个Ising模型.
  • 在单个哺乳动物脑细胞中对数百个基因的mRNA存在/缺失进行分析.

主要成果:

  • 开发的概率模型准确地捕获了基因表达统计数据.
  • 该模型识别了细胞状态概率分布中的多个局部最大值.
  • 根据这些最大值对细胞进行分组会产生与已知的细胞类型一致的分类,并揭示亚型.

结论:

  • 细胞类型和亚型可以从基因表达数据中作为概率状态出现.
  • 最大和Ising模型为单细胞数据分析提供了强大的框架.
  • 这种方法完善了我们对细胞异质性和分类的理解.