Results 181 to 190 of about 130,645 (325)
Advances in Detecting RNA Modifications Using Direct RNA Nanopore Sequencing
This review examines recent advances in Oxford Nanopore Technologies direct RNA sequencing, highlighting its expanding capacity to detect RNA modifications beyond m6A. It discusses computational frameworks and basecalling innovations that enable single‐nucleotide and single‐molecule resolution, explores co‐occurring modifications and their regulatory ...
Yaran Liu, Yang Li, Qiang Sun
wiley +1 more source
Soil microbiomes in degraded grasslands: Assembly, function, and application
The key research priorities for microbial response studies and ecological restoration practices for degraded grasslands. Abstract Grassland ecosystems are pivotal to sustaining multiple ecosystem functions and services like climate regulation, carbon sequestration, and grass production.
Xi‐Lin Yuan +6 more
wiley +1 more source
This study conducted a retrospective analysis of microbiological culture results and antimicrobial resistance patterns in patients with sternal osteomyelitis at a tertiary medical center. The primary pathogens causing sternal osteomyelitis were gram‐positive bacteria. Infections with multidrug‐resistant organisms were also relatively common among these
Yumin Yang +5 more
wiley +1 more source
Functional Characterisation of Microbial Communities Related to Black Stain Formation in Lascaux Cave. [PDF]
Bontemps Z +3 more
europepmc +1 more source
Application of Artificial Intelligence in Clinical Microbiology: From Research to Practice
This paper reviews the application of AI in clinical microbiology practice at home and abroad, including rapid pathogen identification, accurate characterization of microbial resistance patterns, optimization of laboratory workflows, and public health interventions.
Ting Ding, Yi‐Wei Tang, Xiaoke Hao
wiley +1 more source
BioMGCore: A toolkit for detection of biological metabolites in microbiome
The keyword matching and gene proximity principles were used to accurately identify core gene clusters in microbial genomes. The metabolic gene clusters can be classified into different taxonomic groups according to Domain, Phylum, Class, Order, Family, Genus, and Species. BioMGCore can achieve batch statistics for secondary metabolites prediction.
Guang Yang +5 more
wiley +1 more source
Can Amplicon Sequencing Be Replaced by Metagenomics for Biodiversity Inventories? [PDF]
Elliott L, Coissac E.
europepmc +1 more source

