Theoretical Biology and Medical Modelling最新文献

{"title":"Simulation-based assessment of model selection criteria during the application of benchmark dose method to quantal response data.","authors":"Keita Yoshii,&nbsp;Hiroshi Nishiura,&nbsp;Kaoru Inoue,&nbsp;Takayuki Yamaguchi,&nbsp;Akihiko Hirose","doi":"10.1186/s12976-020-00131-w","DOIUrl":"https://doi.org/10.1186/s12976-020-00131-w","url":null,"abstract":"<p><strong>Background: </strong>To employ the benchmark dose (BMD) method in toxicological risk assessment, it is critical to understand how the BMD lower bound for reference dose calculation is selected following statistical fitting procedures of multiple mathematical models. The purpose of this study was to compare the performances of various combinations of model exclusion and selection criteria for quantal response data.</p><p><strong>Methods: </strong>Simulation-based evaluation of model exclusion and selection processes was conducted by comparing validity, reliability, and other model performance parameters. Three different empirical datasets for different chemical substances were analyzed for the assessment, each having different characteristics of the dose-response pattern (i.e. datasets with rich information in high or low response rates, or approximately linear dose-response patterns).</p><p><strong>Results: </strong>The best performing criteria of model exclusion and selection were different across the different datasets. Model averaging over the three models with the lowest three AIC (Akaike information criteria) values (MA-3) did not produce the worst performance, and MA-3 without model exclusion produced the best results among the model averaging. Model exclusion including the use of the Kolmogorov-Smirnov test in advance of model selection did not necessarily improve the validity and reliability of the models.</p><p><strong>Conclusions: </strong>If a uniform methodological suggestion for the guideline is required to choose the best performing model for exclusion and selection, our results indicate that using MA-3 is the recommended option whenever applicable.</p>","PeriodicalId":51195,"journal":{"name":"Theoretical Biology and Medical Modelling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12976-020-00131-w","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38237439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ontological model of multi-agent Smart-system for predicting drug properties based on modified algorithms of artificial immune systems.","authors":"Galina Samigulina, Zarina Samigulina","doi":"10.1186/s12976-020-00130-x","DOIUrl":"10.1186/s12976-020-00130-x","url":null,"abstract":"<p><strong>Background: </strong>Currently, due to the huge progress in the field of information technologies and computer equipment, it is important to use modern approaches of artificial intelligence in order to process extensive chemical information at creating new drugs with desired properties. The interdisciplinary of research creates additional difficulties in creating new drugs. Currently, there are no universal algorithms and software for predicting the \"structure-property\" dependence of drug compounds that can take into account the needs of specialists in this field. In this regard, the development of a modern Smart-system based on the promising bio-inspired approach of artificial immune systems for predicting the structure-property dependence of drug compounds is relevant. The aim of this work is to develop a multi-agent Smart-system for predicting the \"structure-property\" dependence of drug compounds using the ontological approach and modified algorithms of artificial immune systems using the example of drug compounds of the sulfonamide group. The proposed system makes it possible to increase the accuracy of prediction models of the \"structure-property\" dependence, to reduce the time and financial costs for obtaining candidate drug compounds.</p><p><strong>Methods: </strong>During the creation of a Smart-system, there are used multi-agent and ontological approaches, which allow to structure input and output data, optimally to distribute computing resources and to coordinate the work of the system. As a promising approach for processing a large amount of chemical information, extracting informative descriptors and for the creation of an optimal data set, as well as further predicting the properties of medicinal compounds, there are considered modified algorithms of artificial immune systems and various algorithms of artificial intelligence.</p><p><strong>Results: </strong>There was developed an ontological model of a multi-agent Smart-system. There are presented the results of the «structure-property» dependence simulation based on a modified grey wolf optimization algorithm and artificial immune systems. During the simulation, there was used information from the Mol-Instincts sulfonamide descriptor database.</p><p><strong>Conclusion: </strong>The developed multi-agent Smart-system using ontological models allows visually to present the structure and interrelationships of agents functioning, which greatly facilitates the development of software and reduces time and financial costs during the development of new drugs.</p>","PeriodicalId":51195,"journal":{"name":"Theoretical Biology and Medical Modelling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12976-020-00130-x","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38158048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying the annual incidence and underestimation of seasonal influenza: A modelling approach.","authors":"Zachary McCarthy,&nbsp;Safia Athar,&nbsp;Mahnaz Alavinejad,&nbsp;Christopher Chow,&nbsp;Iain Moyles,&nbsp;Kyeongah Nah,&nbsp;Jude D Kong,&nbsp;Nishant Agrawal,&nbsp;Ahmed Jaber,&nbsp;Laura Keane,&nbsp;Sam Liu,&nbsp;Myles Nahirniak,&nbsp;Danielle St Jean,&nbsp;Razvan Romanescu,&nbsp;Jessica Stockdale,&nbsp;Bruce T Seet,&nbsp;Laurent Coudeville,&nbsp;Edward Thommes,&nbsp;Anne-Frieda Taurel,&nbsp;Jason Lee,&nbsp;Thomas Shin,&nbsp;Julien Arino,&nbsp;Jane Heffernan,&nbsp;Ayman Chit,&nbsp;Jianhong Wu","doi":"10.1186/s12976-020-00129-4","DOIUrl":"https://doi.org/10.1186/s12976-020-00129-4","url":null,"abstract":"<p><strong>Background: </strong>Seasonal influenza poses a significant public health and economic burden, associated with the outcome of infection and resulting complications. The true burden of the disease is difficult to capture due to the wide range of presentation, from asymptomatic cases to non-respiratory complications such as cardiovascular events, and its seasonal variability. An understanding of the magnitude of the true annual incidence of influenza is important to support prevention and control policy development and to evaluate the impact of preventative measures such as vaccination.</p><p><strong>Methods: </strong>We use a dynamic disease transmission model, laboratory-confirmed influenza surveillance data, and randomized-controlled trial (RCT) data to quantify the underestimation factor, expansion factor, and symptomatic influenza illnesses in the US and Canada during the 2011-2012 and 2012-2013 influenza seasons.</p><p><strong>Results: </strong>Based on 2 case definitions, we estimate between 0.42-3.2% and 0.33-1.2% of symptomatic influenza illnesses were laboratory-confirmed in Canada during the 2011-2012 and 2012-2013 seasons, respectively. In the US, we estimate between 0.08-0.61% and 0.07-0.33% of symptomatic influenza illnesses were laboratory-confirmed in the 2011-2012 and 2012-2013 seasons, respectively. We estimated the symptomatic influenza illnesses in Canada to be 0.32-2.4 million in 2011-2012 and 1.8-8.2 million in 2012-2013. In the US, we estimate the number of symptomatic influenza illnesses to be 4.4-34 million in 2011-2012 and 23-102 million in 2012-2013.</p><p><strong>Conclusions: </strong>We illustrate that monitoring a representative group within a population may aid in effectively modelling the transmission of infectious diseases such as influenza. In particular, the utilization of RCTs in models may enhance the accuracy of epidemiological parameter estimation.</p>","PeriodicalId":51195,"journal":{"name":"Theoretical Biology and Medical Modelling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12976-020-00129-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38137657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling HIV disease process and progression in seroconversion among South Africa women: using transition-specific parametric multi-state model.","authors":"Zelalem G Dessie, Temesgen Zewotir, Henry Mwambi, Delia North","doi":"10.1186/s12976-020-00128-5","DOIUrl":"10.1186/s12976-020-00128-5","url":null,"abstract":"<p><strong>Background: </strong>HIV infected patients may experience many intermediate events including between-event transition throughout their follow up. Through modelling these transitions, we can gain a deeper understanding of HIV disease process and progression and of factors that influence the disease process and progression pathway. In this work, we present transition-specific parametric multi-state models to describe HIV disease process and progression.</p><p><strong>Methods: </strong>The data is from an ongoing prospective cohort study conducted amongst adult women who were HIV-infected in KwaZulu-Natal, South Africa. Participants were enrolled during the acute HIV infection phase and then followed up during chronic infection, up to ART initiation.</p><p><strong>Results: </strong>Transition specific distributions for multi-state models, including a variety of accelerated failure time (AFT) models and proportional hazards (PH) models, were presented and compared in this study. The analysis revealed that women enrolling with a CD4 count less than 350 cells/mm³ (severe and advanced disease stages) had a far lower chance of immune recovery, and a considerably higher chance of immune deterioration, compared to women enrolling with a CD4 count of 350 cells/mm³ or more (normal and mild disease stages). Our analyses also showed that older age, higher educational levels, higher scores for red blood cell counts, higher mononuclear scores, higher granulocytes scores, and higher physical health scores, all had a significant effect on a shortened time to immunological recovery, while women with many sex partners, higher viral load and larger family size had a significant effect on accelerating time to immune deterioration.</p><p><strong>Conclusion: </strong>Multi-state modelling of transition-specific distributions offers a flexible tool for the study of demographic and clinical characteristics' effects on the entire disease progression pathway. It is hoped that the article will help applied researchers to familiarize themselves with the models, including interpretation of results.</p>","PeriodicalId":51195,"journal":{"name":"Theoretical Biology and Medical Modelling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12976-020-00128-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38072786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk estimation of the SARS-CoV-2 acute respiratory disease outbreak outside China.","authors":"Soyoung Kim,&nbsp;Sunhwa Choi,&nbsp;Youngsuk Ko,&nbsp;Moran Ki,&nbsp;Eunok Jung","doi":"10.1186/s12976-020-00127-6","DOIUrl":"https://doi.org/10.1186/s12976-020-00127-6","url":null,"abstract":"<p><strong>Background: </strong>On December 31, 2019, the World Health Organization was alerted to the occurrence of cases of pneumonia in Wuhan, Hubei Province, China, that were caused by an unknown virus, which was later identified as a coronavirus and named the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to estimate the reproductive number of SARS-CoV-2 in the Hubei Province and evaluate the risk of an acute respiratory coronavirus disease (COVID-19) outbreak outside China by using a mathematical model and stochastic simulations.</p><p><strong>Results: </strong>We constructed a mathematical model of SARS-CoV-2 transmission dynamics, estimated the rate of transmission, and calculated the reproductive number in Hubei Province by using case-report data from January 11 to February 6, 2020. The possible number of secondary cases outside China was estimated by stochastic simulations in various scenarios of reductions in the duration to quarantine and rate of transmission. The rate of transmission was estimated as 0.8238 (95% confidence interval [CI] 0.8095-0.8382), and the basic reproductive number as 4.1192 (95% CI 4.0473-4.1912). Assuming the same rate of transmission as in Hubei Province, the possibility of no local transmission is 54.9% with a 24-h quarantine strategy, and the possibility of more than 20 local transmission cases is 7% outside of China.</p><p><strong>Conclusion: </strong>The reproductive number for SARS-CoV-2 transmission dynamics is significantly higher compared to that of the previous SARS epidemic in China. This implies that human-to-human transmission is a significant factor for contagion in Hubei Province. Results of the stochastic simulation emphasize the role of quarantine implementation, which is critical to prevent and control the SARS-CoV-2 outbreak outside China.</p>","PeriodicalId":51195,"journal":{"name":"Theoretical Biology and Medical Modelling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12976-020-00127-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38014628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational models of melanoma.","authors":"Marco Albrecht, Philippe Lucarelli, Dagmar Kulms, Thomas Sauter","doi":"10.1186/s12976-020-00126-7","DOIUrl":"10.1186/s12976-020-00126-7","url":null,"abstract":"<p><p>Genes, proteins, or cells influence each other and consequently create patterns, which can be increasingly better observed by experimental biology and medicine. Thereby, descriptive methods of statistics and bioinformatics sharpen and structure our perception. However, additionally considering the interconnectivity between biological elements promises a deeper and more coherent understanding of melanoma. For instance, integrative network-based tools and well-grounded inductive in silico research reveal disease mechanisms, stratify patients, and support treatment individualization. This review gives an overview of different modeling techniques beyond statistics, shows how different strategies align with the respective medical biology, and identifies possible areas of new computational melanoma research.</p>","PeriodicalId":51195,"journal":{"name":"Theoretical Biology and Medical Modelling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7222475/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37936905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling the effect of a dengue vaccine on reducing the evolution of resistance against antibiotic due to misuse in dengue cases.","authors":"Ana Kurauchi,&nbsp;Claudio Jose Struchiner,&nbsp;Annelies Wilder-Smith,&nbsp;Eduardo Massad","doi":"10.1186/s12976-020-00125-8","DOIUrl":"https://doi.org/10.1186/s12976-020-00125-8","url":null,"abstract":"<p><strong>Background: </strong>This paper intends to check whether and how a hypothetical dengue vaccine could contribute to issue of evolution of bacteria resistance against antibiotics by reducing the number of patients that would inappropriately being treated with antibiotics.</p><p><strong>Methods: </strong>We use a new mathematical model that combines, in a novel way, two previously published papers, one on the evolution of resistance against antibiotics and one classical Ross-Macdonald model for dengue transmission.</p><p><strong>Results: </strong>The model is simulated numerically and reproduces a real case of evolution of resistance against antibiotics. In addition the model shows that the use of a hypothetical dengue vaccine could help to curb the evolution of resistance against an antibiotic inappropriately used in dengue patients. Both the increase in the proportion of resistant bacteria due to the misuse of antibiotics in dengue cases as a function of the fraction of treated patients and the reduction of that proportion as a function of vaccination coverage occur in a highly non-linear fashion.</p><p><strong>Conclusion: </strong>The use of a dengue vaccine is helpful in reducing the rate of evolution of antibiotic resistance in a scenario of misuse of the antibiotics in dengue patients.</p>","PeriodicalId":51195,"journal":{"name":"Theoretical Biology and Medical Modelling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12976-020-00125-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37931871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling and dynamic analysis of tuberculosis in mainland China from 1998 to 2017: the effect of DOTS strategy and further control.","authors":"Siyu Liu,&nbsp;Yingjie Bi,&nbsp;Yawen Liu","doi":"10.1186/s12976-020-00124-9","DOIUrl":"https://doi.org/10.1186/s12976-020-00124-9","url":null,"abstract":"<p><strong>Background: </strong>Tuberculosis (TB) is one of the most important health topics in the world. Directly observed treatment and short course chemotherapy (DOTS) strategy combines medicine care and modern health system firmly, and it has been carried out by World Health Organization (WHO) since 1997. In the struggle with TB, China has promoted the process of controlling the disease actively, and the full coverage of DOTS strategy has been reached around 2004. Mathematical modeling is a very useful tool to study the transmission of diseases. Understanding the impact of DOTS strategy on the control of TB is important for designing further prevention strategy.</p><p><strong>Methods: </strong>We investigate the impact of control strategy on the transmission of TB in China by dynamic model. Then we discuss further control for TB aiming at developing new vaccine and improving treatment. The optimal control problem, minimizing the total number of infectious individuals with the lowest cost, is proposed and analyzed by Pontryagin's maximum principle. Numerical simulations are provided to illustrate the theoretical results.</p><p><strong>Results: </strong>Theoretical analysis for the epidemic model is given. Based on the data reported by National Bureau of Statistics of China (NBSC), the basic reproduction number of each stage is estimated and compared, and they are [Formula: see text] and [Formula: see text], respectively. Optimal control strategy for further control is designed and proved well. An intuitionistic comparison between the optimal control strategy and the current control strategy is given.</p><p><strong>Conclusions: </strong>The diagnosis and treatment of TB in China have been promoted a lot and the [Formula: see text] is reduced by the full coverage of DOTS strategy. However, the [Formula: see text] in China is still greater than 1 now. The relationship between [Formula: see text] and vaccination strategy is shown. Optimal strategy aiming at exposed and infected population is suggested for further control.</p>","PeriodicalId":51195,"journal":{"name":"Theoretical Biology and Medical Modelling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12976-020-00124-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37895434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An agent-based model to investigate microbial initiation of Alzheimer's via the olfactory system.","authors":"Shalini Sundar, Carly Battistoni, Ryan McNulty, Fernando Morales, Jonathan Gorky, Henry Foley, Prasad Dhurjati","doi":"10.1186/s12976-020-00123-w","DOIUrl":"10.1186/s12976-020-00123-w","url":null,"abstract":"<p><strong>Background: </strong>Alzheimer's disease (AD) is a degenerative brain disease. A novel agent-based modelling framework was developed in NetLogo 3D to provide fundamental insights into the potential mechanisms by which a microbe (eg. Chlamydia pneumoniae) may play a role in late-onset AD. The objective of our initial model is to simulate one possible spatial and temporal pathway of bacterial propagation via the olfactory system, which may then lead to AD symptoms. The model maps the bacteria infecting cells from the nasal cavity and the olfactory epithelium, through the olfactory bulb and into the olfactory cortex and hippocampus regions of the brain.</p><p><strong>Results: </strong>Based on the set of biological rules, simulated randomized infection by the microbe led to the formation of beta-amyloid (Aβ) plaque and neurofibrillary (NF) tangles as well as caused immune responses. Our initial simulations demonstrated that breathing in C. pneumoniae can result in infection propagation and significant buildup of Aβ plaque and NF tangles in the olfactory cortex and hippocampus. Our model also indicated how mucosal and neural immunity can play a significant role in the pathway considered. Lower immunities, correlated with elderly individuals, had quicker and more Aβ plaque and NF tangle formation counts. In contrast, higher immunities, correlated with younger individuals, demonstrated little to no such formation.</p><p><strong>Conclusion: </strong>The modelling framework provides an organized visual representation of how AD progression may occur via the olfactory system to better understand disease pathogenesis. The model confirms current conclusions in available research but can be easily adjusted to match future evidence and be used by researchers for their own individual purposes. The goal of our initial model is to ultimately guide further hypothesis refinement and experimental testing to better understand the dynamic system interactions present in the etiology and pathogenesis of AD.</p>","PeriodicalId":51195,"journal":{"name":"Theoretical Biology and Medical Modelling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12976-020-00123-w","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37833679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Methylation-driven model for analysis of dinucleotide evolution in genomes.","authors":"Jian-Hong Sun,&nbsp;Shi-Meng Ai,&nbsp;Shu-Qun Liu","doi":"10.1186/s12976-020-00122-x","DOIUrl":"https://doi.org/10.1186/s12976-020-00122-x","url":null,"abstract":"<p><strong>Background: </strong>CpGs, the major methylation sites in vertebrate genomes, exhibit a high mutation rate from the methylated form of CpG to TpG/CpA and, therefore, influence the evolution of genome composition. However, the quantitative effects of CpG to TpG/CpA mutations on the evolution of genome composition in terms of the dinucleotide frequencies/proportions remain poorly understood.</p><p><strong>Results: </strong>Based on the neutral theory of molecular evolution, we propose a methylation-driven model (MDM) that allows predicting the changes in frequencies/proportions of the 16 dinucleotides and in the GC content of a genome given the known number of CpG to TpG/CpA mutations. The application of MDM to the 10 published vertebrate genomes shows that, for most of the 16 dinucleotides and the GC content, a good consistency is achieved between the predicted and observed trends of changes in the frequencies and content relative to the assumed initial values, and that the model performs better on the mammalian genomes than it does on the lower-vertebrate genomes. The model's performance depends on the genome composition characteristics, the assumed initial state of the genome, and the estimated parameters, one or more of which are responsible for the different application effects on the mammalian and lower-vertebrate genomes and for the large deviations of the predicted frequencies of a few dinucleotides from their observed frequencies.</p><p><strong>Conclusions: </strong>Despite certain limitations of the current model, the successful application to the higher-vertebrate (mammalian) genomes witnesses its potential for facilitating studies aimed at understanding the role of methylation in driving the evolution of genome dinucleotide composition.</p>","PeriodicalId":51195,"journal":{"name":"Theoretical Biology and Medical Modelling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12976-020-00122-x","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37813362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}