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Pharmacokinetics转录组学技术转录组学技术是用于研究生物体转录组（其所有 RNA 转录本的总和）的技术。生物体的信息内容记录在其基因组的DNA中并通过转录表达。在这里，mRNA 充当信息网络中的瞬时中间分子，而非编码 RNA 则执行其他不同的功能。转录组捕获细胞中存在的总转录本的及时快照。转录组学技术广泛描述了哪些细胞过程是活跃的，哪些是休眠的。分子生物学的一个主要挑战是了解单个基因组如何产生多种细胞。另一个是基因表达的调控方式。研究整个转录组的第一次尝试始于 20 世纪 90 年代初。
Transcriptomics technologies are the techniques used to study an organism's transcriptome, the sum of all of its RNA transcripts. The information content of an organism is recorded in the DNA of its genome and expressed through transcription. Here, mRNA serves as a transient intermediary molecule in the information network, whilst non-coding RNAs perform additional diverse functions. A transcriptome captures a snapshot in time of the total transcripts present in a cell. Transcriptomics technologies provide a broad account of which cellular processes are active and which are dormant. A major challenge in molecular biology is to understand how a single genome gives rise to a variety of cells. Another is how gene expression is regulated. The first attempts to study whole transcriptomes began in the early 1990s.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements. The Chinese definition is a machine-assisted translation of the cited English introduction; check technical terminology against the original.
View content license ↗ 基因表达（英语：gene expression）又称基因表现，是用基因中的信息来合成基因产物的过程。产物通常是蛋白质，但对于非蛋白质编码基因，如tRNA和小核RNA（snRNA），产物则是RNA。所有已知生物都通过基因表达来生成生命所需的高分子物质。 基因表达的过程可概分为：DNA转录、RNA剪接、RNA转译、蛋白质转译后修饰，这四大步骤。基因表达调控控制细胞的结构与功能，同时也是细胞分化、形态发生及生物体的多功能性和适应性的基础。不同的时间、不同的环境，以及不同部位的细胞，或是基因在细胞中的含量差异，皆可能使基因产生不同的表现。基因调节也可以作为进化变化的底物，因为基因表达的时间，位置和数量的控制可以对基因在细胞或多细胞生物体中的功能（作用）具有深远的影响。 在遗传学中，基因表达是基因型产生表现型（即可观察的性状）的最基本的层次。
Gene expression is the process by which the information contained within a gene is used to produce a functional gene product, such as a protein or a functional RNA molecule. This process involves multiple steps, including the transcription of the gene's sequence into RNA. For protein-coding genes, this RNA is further translated into a chain of amino acids that folds into a protein, while for non-coding genes, the resulting RNA itself serves a functional role in the cell. Gene expression enables cells to utilize the genetic information in genes to carry out a wide range of biological functions. While expression levels can be regulated in response to cellular needs and environmental changes, some genes are expressed continuously with little variation.
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View content license ↗ 假发现率（False discovery rate, FDR）完善了对多重假设测试的检验， F D R = Q e = E [ Q ] , {\displaystyle \mathrm {FDR} =Q_{e}=\mathrm {E} \!\left[Q\right],} 其中E表示期望， Q = V / R = V / ( V + S ) {\displaystyle Q=V/R=V/(V+S)} ，V表示错误拒绝零假设的数目，R表示拒绝零假设的数目。R取0时FDR直接取0，写成一句话就是 F D R = E [ V / R | R > 0 ] ⋅ P (…
In statistics, the false discovery rate (FDR) is a method of conceptualizing the rate of type I errors in null hypothesis testing when conducting multiple comparisons. FDR-controlling procedures are designed to control the FDR, which is the expected proportion of "discoveries" (rejected null hypotheses) that are false (incorrect rejections of the null). Equivalently, the FDR is the expected ratio of the number of false positive classifications (false discoveries) to the total number of positive classifications (rejections of the null). The total number of rejections of the null include both the number of false positives (FP) and true positives (TP). Simply put, FDR = FP / (FP + TP). FDR-controlling procedures provide less stringent control of Type I errors compared to family-wise error rate (FWER) controlling procedures (such as the Bonferroni correction), which control the probability of at least one Type I error. Thus, FDR-controlling procedures have greater power, at the cost of increased numbers of Type I errors.
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View content license ↗ 在概率论与统计学中，协方差（英语：Covariance）用于衡量随机变量间的相关程度。
In probability theory and statistics, covariance is a measure of the joint variability of two random variables. The sign of the covariance shows the tendency in the linear relationship between the variables. Covariance is positive when variables tend to show similar behavior and negative when variables tend to show opposite behavior. The magnitude of the covariance is the geometric mean of the variances that are shared for the two random variables, where a larger magnitude means two variables more strongly depend on each other. Covariance has units of measurement, and the magnitude of the covariance is affected by said units. This means changing the units (e.g., from meters to millimeters) changes the covariance value proportionally, making it difficult to assess the strength of the relationship from the covariance alone.
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View content license ↗ 在统计学中，最大似然估计 (MLE) 是一种在给定一些观测数据的情况下估计假设概率分布参数的方法。这是通过最大化似然函数来实现的，以便在假设的统计模型下，观察到的数据是最可能的。参数空间中使似然函数最大化的点称为最大似然估计。最大似然法的逻辑既直观又灵活，因此该方法已成为统计推断的主要手段。如果似然函数可微，则可以应用求最大值的导数检验。
In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data. This is achieved by maximizing a likelihood function so that, under the assumed statistical model, the observed data is most probable. The point in the parameter space that maximizes the likelihood function is called the maximum likelihood estimate. The logic of maximum likelihood is both intuitive and flexible, and as such the method has become a dominant means of statistical inference. If the likelihood function is differentiable, the derivative test for finding maxima can be applied.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements. The Chinese definition is a machine-assisted translation of the cited English introduction; check technical terminology against the original.
View content license ↗ 系统发育的贝叶斯推理结合了先验和数据似然中的信息来创建所谓的树的后验概率，即给定数据、先验和似然模型时树正确的概率。贝叶斯推理在 20 世纪 90 年代被三个独立的小组引入分子系统发育学：伯克利的 Bruce Rannala 和 Ziheng Yang、麦迪逊的 Bob Mau 以及爱荷华大学的 Shuying Li，最后两位当时是博士生。自 2001 年 MrBayes 软件发布以来，该方法变得非常流行，现在是分子系统发育学中最流行的方法之一。
Bayesian inference of phylogeny combines the information in the prior and in the data likelihood to create the so-called posterior probability of trees, which is the probability that the tree is correct given the data, the prior and the likelihood model. Bayesian inference was introduced into molecular phylogenetics in the 1990s by three independent groups: Bruce Rannala and Ziheng Yang in Berkeley, Bob Mau in Madison, and Shuying Li in University of Iowa, the last two being PhD students at the time. The approach has become very popular since the release of the MrBayes software in 2001, and is now one of the most popular methods in molecular phylogenetics.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements. The Chinese definition is a machine-assisted translation of the cited English introduction; check technical terminology against the original.
View content license ↗ 在概率论中，隐马尔可夫模型（HMM）是一种马尔可夫模型，其中观测值依赖于潜在（或隐藏）马尔可夫过程（称为 X {\displaystyle X} ）。 HMM 要求存在一个可观察过程 Y {\displaystyle Y}，其结果以已知方式取决于 X {\displaystyle X} 的结果。由于 X {\displaystyle X} 无法直接观察，因此目标是通过观察 Y {\displaystyle Y} 来了解 X {\displaystyle X} 的状态。
In probability theory, a hidden Markov model (HMM) is a Markov model in which the observations are dependent on a latent (or hidden) Markov process (referred to as X {\displaystyle X} ). An HMM requires that there be an observable process Y {\displaystyle Y} whose outcomes depend on the outcomes of X {\displaystyle X} in a known way. Since X {\displaystyle X} cannot be observed directly, the goal is to learn about state of X {\displaystyle X} by observing Y {\displaystyle Y} .
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements. The Chinese definition is a machine-assisted translation of the cited English introduction; check technical terminology against the original.
View content license ↗ 区室模型是一种数学框架，用于模拟人口如何在不同状态或“区室”之间移动。虽然广泛应用于各个领域，但它们对于传染病的数学建模尤其重要。在这些模型中，人群被划分为用简写符号标记的区域——最常见的是 S、I 和 R，代表易感个体、感染个体和康复个体。字母顺序通常表示隔室之间的流动模式；例如，SEIS 模型代表从易感性到暴露于传染性，然后再次回到易感性的进展。这些模型起源于 20 世纪初几位数学家开创性的流行病学工作。
Compartmental models are a mathematical framework used to simulate how populations move between different states or "compartments". While widely applied in various fields, they have become particularly fundamental to the mathematical modelling of infectious diseases. In these models, the population is divided into compartments labeled with shorthand notation – most commonly S, I, and R, representing Susceptible, Infectious, and Recovered individuals. The sequence of letters typically indicates the flow patterns between compartments; for example, an SEIS model represents progression from susceptible to exposed to infectious and then back to susceptible again. These models originated in the early 20th century through pioneering epidemiological work by several mathematicians.
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View content license ↗ 标定（英语：Calibration），即为科学上之校准行为，意指“对某仪器、药物或须有精确单位之物品，其只知的体积、浓度......等刻度或单位之准确度，进行检测是否合乎标准，若否则修正。”
In measurement technology and metrology, calibration is the comparison of measurement values delivered by a device under test with those of a calibration standard of known accuracy. Such a standard could be another measurement device of known accuracy, a device generating the quantity to be measured such as a voltage, a sound tone, or a physical artifact, such as a meter ruler. The outcome of the comparison can result in one of the following: no significant error being noted on the device under test a significant error being noted but no adjustment made an adjustment made to correct the error to an acceptable level Strictly speaking, the term "calibration" means just the act of comparison and does not include any subsequent adjustment. The calibration standard is normally traceable to a national or international standard held by a metrology body.
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View content license ↗ 不确定性量化（UQ）是对计算和现实世界应用中的不确定性进行定量表征和估计的科学。它试图确定如果系统的某些方面不完全已知的话某些结果的可能性有多大。一个例子是预测人体与另一辆车正面相撞时的加速度：即使速度是准确已知的，个别汽车制造过程中的微小差异、每个螺栓的拧紧程度等都会导致不同的结果，而这些结果只能在统计意义上进行预测。自然科学和工程学中的许多问题也充满了不确定性。计算机模拟的计算机实验是研究不确定性量化问题的最常见方法。
Uncertainty Quantification (UQ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system are not exactly known. An example would be to predict the acceleration of a human body in a head-on crash with another car: even if the speed was exactly known, small differences in the manufacturing of individual cars, how tightly every bolt has been tightened, etc., will lead to different results that can only be predicted in a statistical sense. Many problems in the natural sciences and engineering are also rife with sources of uncertainty. Computer experiments on computer simulations are the most common approach to study problems in uncertainty quantification.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements. The Chinese definition is a machine-assisted translation of the cited English introduction; check technical terminology against the original.
View content license ↗ 在数值分析中，数值方法是一种旨在解决数值问题的数学工具。用编程语言实现具有适当收敛性检查的数值方法称为数值算法。
In numerical analysis, a numerical method is a mathematical tool designed to solve numerical problems. The implementation of a numerical method with an appropriate convergence check in a programming language is called a numerical algorithm.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements. The Chinese definition is a machine-assisted translation of the cited English introduction; check technical terminology against the original.
View content license ↗ 微分方程（英语：Differential equation，DE）是一种数学方程，用来描述某一类函数与其导数之间的关系。微分方程的解是一个满足方程的函数，通常微分方程的解并不唯一，经常要给定恰当的初始条件或边界条件才能确定。而在初等数学的代数方程里，其解是常数。 微分方程的应用十分广泛，可以解决许多与导数有关的问题。物理学中许多涉及变力的运动学、动力学问题，如空气阻力为速度函数的自由落体运动等问题，很多可以用微分方程求解。此外，微分方程在化学、工程学、经济学和数理生物学等领域都有应用。 数学领域对微分方程的研究着重在几个不同的面向，但大多数都是关心微分方程的解。只有少数简单的微分方程可以求得解析解。不过即使没有找到其解析解，仍然可以确认其解的部分性质。在无法求得解析解时，可以利用数值分析的方式，利用电脑来找到其数值解。 动力系统理论强调对于微分方程系统的量化分析，而许多数值方法可以计算微分方程的数值解，且有一定的准确度。
In mathematics, a differential equation is an equation that relates one or more unknown functions and their derivatives. In applications, the functions generally represent physical quantities, the derivatives represent their rates of change, and the differential equation defines a relationship between the two. Such relations are common in mathematical models and scientific laws; therefore, differential equations play a prominent role in many disciplines including engineering, physics, economics, and biology. The study of differential equations consists mainly of the study of their solutions (the set of functions that satisfy each equation), and of the properties of their solutions. Only the simplest differential equations are solvable by explicit formulas; however, many properties of solutions of a given differential equation may be determined without computing them exactly.
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View content license ↗ 在微分方程中，边值问题是一个微分方程和一组称之为边界条件的约束条件。边值问题的解通常是符合约束条件的微分方程的解。 物理学中经常遇到边值问题，例如波动方程等。许多重要的边值问题属于Sturm-Liouville问题。这类问题的分析会和微分算子的本征函数有关。 在实际应用中，边值问题应当是适定的（即：存在解，解唯一且解会随着初始值连续地变化）。许多偏微分方程领域的理论提出是为要证明科学及工程应用的许多边值问题都是适定问题。 最早研究的边值问题是狄利克雷问题，是要找出调和函数，也就是拉普拉斯方程的解，后来是用狄利克雷原理找到相关的解。
In the study of differential equations, a boundary-value problem is a differential equation subjected to constraints called boundary conditions. A solution to a boundary value problem is a solution to the differential equation which also satisfies the boundary conditions. Boundary value problems arise in several branches of physics as any physical differential equation will have them. Problems involving the wave equation, such as the determination of normal modes, are often stated as boundary value problems. A large class of important boundary value problems are the Sturm–Liouville problems. The analysis of these problems, in the linear case, involves the eigenfunctions of a differential operator. To be useful in applications, a boundary value problem should be well posed. This means that given the input to the problem there exists a unique solution, which depends continuously on the input.
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View content license ↗ 在泛函分析中，卷积（convolution），或译为叠积、褶积或旋积，是透过两个函数 f {\displaystyle f} 和 g {\displaystyle g} 生成第三个函数的一种数学算子，表征函数 f {\displaystyle f} 与经过翻转和平移的 g {\displaystyle g} 的乘积函数所围成的曲边梯形的面积。如果将参加卷积的一个函数看作区间的指示函数，卷积还可以被看作是“移动平均”的推广。
In mathematics (in particular, functional analysis), convolution is a mathematical operation on two functions f {\displaystyle f} and g {\displaystyle g} that produces a third function f ∗ g {\displaystyle f*g} , as the integral of the product of the two functions after one is reflected about the y-axis and shifted. The term convolution refers to both the resulting function and to the process of computing it. The integral is evaluated for all values of shift, producing the convolution function. The choice of which function is reflected and shifted before the integral does not change the integral result (see commutativity). Graphically, it expresses how the 'shape' of one function is modified by the other.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 拉普拉斯变换（英语：Laplace transform）是应用数学中常用的一种积分变换，又名拉氏变换，其符号为 L { f ( t ) } {\displaystyle \displaystyle {\mathcal {L}}\left\{f(t)\right\}} 。拉氏变换是一个线性变换，可将一个有实数变量 t ( t ≥ 0 ) {\displaystyle t(t\geq 0)} 的函数变换为一个变量为复数 s {\displaystyle s} 的函数： F ( s ) = ∫ 0 ∞ f ( t ) e − s t d t .
In mathematics, the Laplace transform, named after Pierre-Simon Laplace (), is an integral transform that converts a function of a real variable (usually t {\displaystyle t} , in the time domain) to a function of a complex variable s {\displaystyle s} (in the complex-valued frequency domain, also known as s-domain or s-plane). The functions are often denoted using a lowercase symbol for the time-domain function and the corresponding uppercase symbol for the frequency-domain function, e.g. x ( t ) {\displaystyle x(t)} and X ( s ) {\displaystyle X(s)} . The transform is useful for converting differentiation and integration in the time domain into the algebraic operations multiplication and division in the Laplace domain (analogous to how logarithms are useful for simplifying multiplication and division into addition and subtraction).
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View content license ↗ 菲克定律（英语：Fick's law）描述扩散作用，可以使用这条定律来求得扩散系数：D。定律由德国生理学家阿道夫·菲克于1855年推导出来。
Fick's laws of diffusion describe diffusion and were first posited by Adolf Fick in 1855 on the basis of largely experimental results. They can be used to solve for the diffusion coefficient, D {\displaystyle D} . Fick's first law can be used to derive his second law, which in turn is identical to the diffusion equation. Fick's first law: Movement of particles from high to low concentration (diffusive flux) is directly proportional to the particle's concentration gradient. Fick's second law: Prediction of change in concentration gradient with time due to diffusion. A diffusion process that obeys Fick's laws is called normal or Fickian diffusion; otherwise, it is called anomalous diffusion or non-Fickian diffusion.
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View content license ↗ 扩散是任何事物（例如原子、离子、分子、能量）通常从较高浓度区域到较低浓度区域的净运动。扩散是由吉布斯自由能或化学势的梯度驱动的。可以从较低浓度区域“上坡”扩散到较高浓度区域，如旋节线分解。由于扩散实体固有的随机性，扩散是一个随机过程，可用于模拟许多现实生活中的随机场景。因此，扩散和相应的数学模型被应用于物理学以外的多个领域，例如统计学、概率论、信息论、神经网络、金融和营销。
Diffusion is the net movement of anything (for example, atoms, ions, molecules, energy) generally from a region of higher concentration to a region of lower concentration. Diffusion is driven by a gradient in Gibbs free energy or chemical potential. It is possible to diffuse "uphill" from a region of lower concentration to a region of higher concentration, as in spinodal decomposition. Diffusion is a stochastic process due to the inherent randomness of the diffusing entity and can be used to model many real-life stochastic scenarios. Therefore, diffusion and the corresponding mathematical models are used in several fields beyond physics, such as statistics, probability theory, information theory, neural networks, finance, and marketing.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements. The Chinese definition is a machine-assisted translation of the cited English introduction; check technical terminology against the original.
View content license ↗ 朗缪尔吸附模型（英语：Langmuir adsorption model）也常被称为朗缪尔吸附等温式。这一模型假设在等温吸附过程中，吸附质的分子与理想气体的分子类似，吸附和解吸是一对可逆过程。也解释了吸附质的分压 p A {\displaystyle p_{A}} 与固体吸附剂上吸附质的体积之间的关系。其中的吸附剂被假设为一个理想的固体表面，具有一系列能够与吸附质结合的位点。这种结合被视作气相的吸附质分子 A g {\displaystyle A_{\text{g}}} 和空的位点S的相互作用。
The Langmuir adsorption model explains adsorption by assuming an adsorbate behaves as an ideal gas at isothermal conditions. According to the model, adsorption and desorption are reversible processes. This model even explains the effect of pressure; i.e., at these conditions the adsorbate's partial pressure p A {\displaystyle p_{A}} is related to its volume V adsorbed onto a solid adsorbent. The adsorbent, as indicated in the figure, is assumed to be an ideal solid surface composed of a series of distinct sites capable of binding the adsorbate. The adsorbate binding is treated as a chemical reaction between the adsorbate gaseous molecule A g {\displaystyle A_{\text{g}}} and an empty sorption site S.
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View content license ↗ 非房室分析利用浓度时间曲线的面积、终末斜率和统计矩估计暴露与药代指标，不预先指定完整房室结构。采样范围和外推比例会影响可靠性。
Noncompartmental analysis estimates exposure and pharmacokinetic measures from curve areas, terminal slopes and statistical moments without specifying a full compartment model. Sampling and extrapolation affect reliability.
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SciAtlas original bilingual definition · Edited2026-10-04 · CC BY-SA 4.0. Further-reading links provide context; the definition is original and does not assert that the linked page was retrieved or checked.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 群体药代动力学同时描述典型药代行为、个体差异和观测误差，并研究协变量影响。模型参数应结合数据支持程度和诊断结果解释。
Population pharmacokinetics jointly models typical kinetics, between-subject variability and observation error while studying covariates. Parameters must be interpreted with data support and diagnostic evidence.
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SciAtlas original bilingual definition · Edited2026-10-04 · CC BY-SA 4.0. Further-reading links provide context; the definition is original and does not assert that the linked page was retrieved or checked.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 视觉预测检验通过模型模拟数据分布与实际观测分布比较来评估模型表现。分层、分箱和预测校正选择会影响图形，不是单一通过证明。
A visual predictive check compares simulated and observed distributions to assess model behavior. Stratification, binning and prediction correction affect interpretation; a favorable plot is not a universal validation proof.
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SciAtlas original bilingual definition · Edited2026-10-04 · CC BY-SA 4.0. Further-reading links provide context; the definition is original and does not assert that the linked page was retrieved or checked.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 定量下限是在规定精密度和准确度要求下可以定量报告的最低浓度，属于方法验证条件。低于该值的数据处理方式需要在分析计划中说明。
The lower limit of quantification is the lowest concentration reportable under specified precision and accuracy requirements. Handling observations below it must be defined in the analysis plan.
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SciAtlas original bilingual definition · Edited2026-10-04 · CC BY-SA 4.0. Further-reading links provide context; the definition is original and does not assert that the linked page was retrieved or checked.For concept reference; consult the original standards for authoritative requirements.
View content license ↗