Instantaneous maturity rate: a novel and compact characterization of biological growth curve models

IF 1.8 4区 生物学 Q3 BIOPHYSICS Journal of Biological Physics Pub Date : 2022-07-02 DOI:10.1007/s10867-022-09609-9
Biman Chakraborty, Amiya Ranjan Bhowmick, Joydev Chattopadhyay, Sabyasachi Bhattacharya
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引用次数: 1

Abstract

Modeling and analysis of biological growth curves are an age-old study area in which much effort has been dedicated to developing new growth equations. Recent efforts focus on identifying the correct model from a large number of equations. The relative growth rate (RGR), developed by Fisher (1921), has largely been used in the statistical inference of biological growth curve models. It is convenient to express growth equations using RGR, where RGR can be expressed as functions of size or time. Even though RGR is model invariant, it has limitations when it comes to identifying actual growth patterns. By proposing interval-specific rate parameters (ISRPs), Pal et al. (2018) appeared to solve this problem. The ISRP is based on the mathematical structure of the growth equations. Therefore, it is not model invariant. The current effort is to develop a measure of growth that is model invariant like RGR and shares the advantages of ISRP. We propose a new measure of growth, which we call instantaneous maturity rate (IMR). IMR is model invariant, which allows it to distinguish growth patterns more clearly than RGR. IMR is also scale-invariant and can take several forms including increasing, decreasing, constant, sigmoidal, bell-shaped, and bathtub. A wide range of possible IMR shapes makes it possible to identify different growth curves. The estimation procedure of IMR under a stochastic setup has been developed. Statistical properties of empirical IMR estimators have also been investigated in detail. In addition to extensive simulation studies, real data sets have been analyzed to prove the utility of IMR.

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瞬时成熟率:一种新颖而紧凑的生物生长曲线模型
生物生长曲线的建模和分析是一个古老的研究领域,人们一直致力于开发新的生长方程。最近的努力集中在从大量的方程中找出正确的模型。由Fisher(1921)提出的相对生长率(RGR)在生物生长曲线模型的统计推断中得到了广泛的应用。用RGR表示生长方程很方便,其中RGR可以表示为大小或时间的函数。尽管RGR是模型不变的,但在识别实际增长模式时,它也有局限性。Pal等人(2018)通过提出间隔特定速率参数(isrp),似乎解决了这一问题。ISRP是基于生长方程的数学结构。因此,它不是模型不变的。目前的努力是开发一种像RGR一样模型不变的增长衡量标准,并分享ISRP的优势。我们提出了一种新的增长度量,我们称之为瞬时成熟度(IMR)。IMR是模型不变性的,这使得它比RGR更清楚地区分增长模式。IMR也是尺度不变的,可以采取几种形式,包括增加,减少,常数,s形,钟形和浴缸。广泛的可能的IMR形状使得识别不同的生长曲线成为可能。给出了随机设置下的IMR估计方法。本文还详细研究了经验IMR估计器的统计性质。除了广泛的模拟研究外,还分析了实际数据集来证明IMR的实用性。
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来源期刊
Journal of Biological Physics
Journal of Biological Physics 生物-生物物理
CiteScore
3.00
自引率
5.60%
发文量
20
审稿时长
>12 weeks
期刊介绍: Many physicists are turning their attention to domains that were not traditionally part of physics and are applying the sophisticated tools of theoretical, computational and experimental physics to investigate biological processes, systems and materials. The Journal of Biological Physics provides a medium where this growing community of scientists can publish its results and discuss its aims and methods. It welcomes papers which use the tools of physics in an innovative way to study biological problems, as well as research aimed at providing a better understanding of the physical principles underlying biological processes.
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