Chemoinformatics-driven classification of Angiosperms using sulfur-containing compounds and machine learning algorithm.

ABSTRACT:

Background

Phytochemicals or secondary metabolites are low molecular weight organic compounds with little function in plant growth and development. Nevertheless, the metabolite diversity govern not only the phenetics of an organism but may also inform the evolutionary pattern and adaptation of green plants to the changing environment. Plant chemoinformatics analyzes the chemical system of natural products using computational tools and robust mathematical algorithms. It has been a powerful approach for species-level differentiation and is widely employed for species classifications and reinforcement of previous classifications.

Results

This study attempts to classify Angiosperms using plant sulfur-containing compound (SCC) or sulphated compound information. The SCC dataset of

SUBMITTER: Abdullah-Zawawi MR 

PROVIDER: S-EPMC9636760 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature