NEW USE OF MACHINE LEARNING IN BIOINFORMATICS

Abstract

With the help of sequence data, gene function and the secondary structure of RNA can each be inferred. If facts are contained inside genes, then proteins are the laborers who turn this record into domestic affairs. Proteins are known to play an important role in the process of survival, and the 3-dimensional (3-D) shape they possess is an important component of their functionality. Protein size prediction is a primary use of computational tools within the proteomics field. Proteins are quite complex polymers with thousands of atoms and boundaries in their structure. The strategies used in systems mastering are also used in the practice of evolution and, in particular, in the reconstruction of phylogenetic trees. The evolution of species can be shown in a simplified shapefile using phylogenetic trees.

Keywords

Machine, , Learning, phylogenetic trees, computational tools, 3-dimensional