Phylogenetic analysis based on Machine Learning Algorithm
The interpretation of the phylogenetic tree is an essential yet challenging aspect of evolutionary studies. To conduct an evolutionary study of the organisms is the core of biological research. The resulting phylogeny is then subjected to a plethora of analyses essential for further genomic research (Azouri 2021). The phylogenetic analysis involves several methods that can be used to interpret data. Recently, researchers have begun studying the use of machine learning in inferring phylogenetic trees. Contact:
The interpretation of the phylogenetic tree is an essential yet challenging aspect of evolutionary studies. To conduct an evolutionary study of the organisms is the core of biological research. The resulting phylogeny is then subjected to a plethora of analyses essential for further genomic research (Azouri 2021). The phylogenetic analysis involves several methods that can be used to interpret data. Recently, researchers have begun studying the use of machine learning in inferring phylogenetic trees.
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They showed that both these methods are reliable and can be applied for handling
large-scale datasets.
They also highlighted the ability of these techniques over the heuristic-based
techniques to automatically learn complicated inter-variable associations.
Their research can also be used as a model for applying machine learning methods to
the phylogenetic analysis (Bhattacharjee 2020).
In another research, a machine learning framework was developed to rank the
neighbouring trees in accordance with their prosperity to increase the likelihood.
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