Maximum Likelihood Method on The Construction of Phylogenetic Tree for Identification the Spreading of SARS Epidemic

Amiroch, Siti; Pradana, Mohammad Syaiful; Irawan, Mohammad Isa; Mukhlash, Imam

doi:10.1109/sain.2018.8673334

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…In order to analyze the transmission route of the MERS, decision tree and apriori algorithms were used in [20]. In [21] a maximum likelihood method was used to assess the spread of the SARS epidemic using the construction of phylogenetic tree. In [22] SVM was used to address the same issue.…”

Section: Introductionmentioning

confidence: 99%

Forecasting Models for Coronavirus Disease (COVID-19): A Survey of the State-of-the-Art

et al. 2020

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COVID-19 is a pandemic that has affected over 170 countries around the world. The number of infected and deceased patients has been increasing at an alarming rate in almost all the affected nations. Forecasting techniques can be inculcated thereby assisting in designing better strategies and in taking productive decisions. These techniques assess the situations of the past thereby enabling better predictions about the situation to occur in the future. These predictions might help to prepare against possible threats and consequences. Forecasting techniques play a very important role in yielding accurate predictions. This study categorizes forecasting techniques into two types, namely, stochastic theory mathematical models and data science/ machine learning techniques. Data collected from various platforms also play a vital role in forecasting. In this study, two categories of datasets have been discussed, i.e., big data accessed from World Health Organization/National databases and data from a social media communication. Forecasting of a pandemic can be done based on various parameters such as the impact of environmental factors, incubation period, the impact of quarantine, age, gender and many more. These techniques and parameters used for forecasting are extensively studied in this work. However, forecasting techniques come with their own set of challenges (technical and generic). This study discusses these challenges and also provides a set of recommendations for the people who are currently fighting the global COVID-19 pandemic.

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Section: Introductionmentioning

confidence: 99%

Forecasting Models for Coronavirus Disease (COVID-19): A Survey of the State-of-the-Art

et al. 2020

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“…The GTR model assumes that all nucleotides occur at different frequencies and convert at different rates. Next, a tree space search is conducted, and optimal substitution parameters and branch lengths for each topology are optimized based on standard numerical optimization principles to maximize the likelihood value for each topology [49,50]. Finally, the topology with the highest ML value is selected as the optimal evolutionary tree.…”

Section: Maximum Likelihood (Ml) Methodsmentioning

confidence: 99%

Common Methods for Phylogenetic Tree Construction and Their Implementation in R

Zou,

Zhang,

Zeng

et al. 2024

Bioengineering

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A phylogenetic tree can reflect the evolutionary relationships between species or gene families, and they play a critical role in modern biological research. In this review, we summarize common methods for constructing phylogenetic trees, including distance methods, maximum parsimony, maximum likelihood, Bayesian inference, and tree-integration methods (supermatrix and supertree). Here we discuss the advantages, shortcomings, and applications of each method and offer relevant codes to construct phylogenetic trees from molecular data using packages and algorithms in R. This review aims to provide comprehensive guidance and reference for researchers seeking to construct phylogenetic trees while also promoting further development and innovation in this field. By offering a clear and concise overview of the different methods available, we hope to enable researchers to select the most appropriate approach for their specific research questions and datasets.

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“…Through the examination of genetic sequences, morphological traits or behaviour patterns, phylogenetic trees are constructed to illustrate branching points and divergence times in evolutionary history. These trees, constructed using statistical methods such as maximum likelihood (Steel and Rodrigo, 2008;Amiroch et al, 2018) or Bayesian interference (Makarenkov et al, 2006;Boussau et al, 2013), enable the estimation of ancestral states and the anticipation of future evolutionary trajectories. Phylogenetic analysis has been successfully used to predict growth rates of soil bacteria (Walkup et al, 2023), plant bioprospecting (Saslis-Lagoudakis et al, 2012) and identifying evolutionary drivers of mammalian brain development (Barton and Harvey, 2000).…”

Section: Phylogenetic Comparison Modelsmentioning

confidence: 99%

Unravelling the factors of evolutionary repeatability: insights and perspectives on predictability in evolutionary biology

Pearless,

Freed

2024

Front. Ecol. Evol.

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Evolutionary biology was previously considered a historical science with predictions about evolutionary trajectories believed to be near impossible. The development of high throughput sequencing and data analysis technologies has challenged this belief, and provided an abundance of data that yields novel insights into evolutionary processes. Evolutionary predictions are now increasingly being used to develop fundamental knowledge of evolving systems and/or to demonstrate evolutionary control. Here we investigate the factors that make evolutionary repeatability more or less likely to increase the accuracy of evolutionary predictions. We identify outstanding questions and provide a potential starting point to determine how evolutionary repeatability is affected by genetic relatedness.

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Maximum Likelihood Method on The Construction of Phylogenetic Tree for Identification the Spreading of SARS Epidemic

Cited by 4 publications

References 13 publications

Forecasting Models for Coronavirus Disease (COVID-19): A Survey of the State-of-the-Art

Forecasting Models for Coronavirus Disease (COVID-19): A Survey of the State-of-the-Art

Common Methods for Phylogenetic Tree Construction and Their Implementation in R

Unravelling the factors of evolutionary repeatability: insights and perspectives on predictability in evolutionary biology

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