Cargando…
Chemoinformatics-driven classification of Angiosperms using sulfur-containing compounds and machine learning algorithm
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 gree...
Autores principales: | Abdullah-Zawawi, Muhammad-Redha, Govender, Nisha, Karim, Mohammad Bozlul, Altaf-Ul-Amin, Md., Kanaya, Shigehiko, Mohamed-Hussein, Zeti-Azura |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9636760/ https://www.ncbi.nlm.nih.gov/pubmed/36335358 http://dx.doi.org/10.1186/s13007-022-00951-6 |
Ejemplares similares
-
Potential Arabidopsis thaliana glucosinolate genes identified from the co-expression modules using graph clustering approach
por: Harun, Sarahani, et al.
Publicado: (2021) -
Genome-wide analysis of sulfur-encoding biosynthetic genes in rice (Oryza sativa L.) with Arabidopsis as the sulfur-dependent model plant
por: Abdullah-Zawawi, Muhammad-Redha, et al.
Publicado: (2022) -
SuCComBase: a manually curated repository of plant sulfur-containing compounds
por: Harun, Sarahani, et al.
Publicado: (2019) -
Antibacterial Activity Prediction of Plant Secondary Metabolites Based on a Combined Approach of Graph Clustering and Deep Neural Network
por: Karim, Mohammad Bozlul, et al.
Publicado: (2022) -
Multi-Omics Approaches and Resources for Systems-Level Gene Function Prediction in the Plant Kingdom
por: Abdullah-Zawawi, Muhammad-Redha, et al.
Publicado: (2022)