Affiliation:
1. Instituto de Química, Universidad Nacional Autónoma de México, Ciudad de México, México
2. Facultad de Química, Universidad Nacional Autónoma de México, Ciudad de México, México
Abstract
AbstractThe discovery of novel antimicrobials has significantly slowed down over the last three decades. At the same time, humans rely increasingly on antimicrobials because of the progressive
antimicrobial resistance in medical practices, human communities, and the environment. Data mining is currently considered a promising option in the discovery of new antibiotics. Some of the
advantages of data mining are the ability to predict chemical structures from sequence data, anticipation of the presence of novel metabolites, the understanding of gene evolution, and the
corroboration of data from multiple omics technologies. This review analyzes the state-of-the-art for data mining in the fields of bacteria, fungi, and plant genomic data, as well as
metabologenomics. It also summarizes some of the most recent research accomplishments in the field, all pinpointing to innovation through uncovering and implementing the next generation of
antimicrobials.
Funder
Consejo Nacional de Ciencia y Tecnología
Facultad de Química, Universidad Nacional Autonoma de México
Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México
Subject
Organic Chemistry,Complementary and alternative medicine,Drug Discovery,Pharmaceutical Science,Pharmacology,Molecular Medicine,Analytical Chemistry
Cited by
2 articles.
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