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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In this method, the two sequences are stacked in a way to highlight their common
symbols and substrings.
This comparison of sequences helps to identify patterns of shared ancestry between
species.
(Munjal 2019). However, exploiting these large-scale molecular data poses
significant challenges.
One of the most difficult tasks is to develop effective techniques for the extraction of
missing data.
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