A stochastic programming approach to the antibiotics time machine problem

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-04-10 DOI:10.1016/j.mbs.2024.109191

Oğuz Mesüm, Ali Rana Atilgan, Burak Kocuk

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引用次数: 0

Abstract

Antibiotics Time Machine is an important problem to understand antibiotic resistance and how it can be reversed. Mathematically, it can be modeled as follows: Consider a set of genotypes, each of which contain a set of mutated and unmutated genes. Suppose that a set of growth rate measurements of each genotype under a set of antibiotics is given. The transition probabilities of a ‘realization’ of a Markov chain associated with each arc under each antibiotic are computable via a predefined function given the growth rate realizations. The aim is to maximize the expected probability of reaching to the genotype with all unmutated genes given the initial genotype in a predetermined number of transitions, considering the following two sources of uncertainties: (i) the randomness in growth rates, (ii) the randomness in transition probabilities, which are functions of growth rates. We develop stochastic mixed-integer linear programming and dynamic programming approaches to solve static and dynamic versions of the Antibiotics Time Machine Problem under the aforementioned uncertainties. We adapt a Sample Average Approximation approach that exploits the special structure of the problem and provide accurate solutions that perform very well in an out-of-sample analysis.

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抗生素时间机器问题的随机编程方法

抗生素时间机器是了解抗生素耐药性及其逆转方法的一个重要问题。它的数学模型如下：考虑一组基因型，每种基因型都包含一组变异和未变异的基因。假设给出了每种基因型在一组抗生素作用下的生长率测量值。在每种抗生素作用下，与每个弧相关联的马尔可夫链的 "实现 "的过渡概率可通过给定增长率实现值的预定函数来计算。考虑到以下两个不确定性来源：(i) 生长率的随机性；(ii) 过渡概率的随机性，而过渡概率是生长率的函数。我们开发了随机混合整数线性规划和动态规划方法，以解决上述不确定性下的抗生素时间机器问题的静态和动态版本。我们采用了一种样本平均近似方法，该方法利用了问题的特殊结构，并提供了在样本外分析中表现优异的精确解决方案。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.