Results 51 to 60 of about 563,010 (309)
Enteropathogenic E. coli (EPEC) infects the human intestinal epithelium, resulting in severe illness and diarrhoea. In this study, we compared the infection of cancer‐derived cell lines with human organoid‐derived models of the small intestine. We observed a delayed in attachment, inflammation and cell death on primary cells, indicating that host ...
Mastura Neyazi +5 more
wiley +1 more source
Predicting antimicrobial resistance using conserved genes
AbstractA growing number of studies have shown that machine learning algorithms can be used to accurately predict antimicrobial resistance (AMR) phenotypes from bacterial sequence data. In these studies, models are typically trained using input features derived from comprehensive sets of known AMR genes or whole genome sequences.
Marcus Nguyen +4 more
openaire +5 more sources
Organoids in pediatric cancer research
Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley +1 more source
Gene prediction: compare and CONTRAST [PDF]
CONTRAST, a new gene-prediction algorithm that uses sophisticated machine-learning techniques, has pushed de novo prediction accuracy to new heights, and has significantly closed the gap between de novo and evidence-based methods for human genome annotation.
openaire +2 more sources
In this study, we present the structure of AcrIE8.1, a previously uncharacterized anti‐CRISPR protein that inhibits the type I‐E CRISPR‐Cas system. Through a combination of structural and biochemical analyses, we demonstrate that AcrIE8.1 directly binds to the Cas11 subunit of the Cascade complex to inhibit the CRISPR‐Cas system.
Young Woo Kang, Hyun Ho Park
wiley +1 more source
Microarray-Based Cancer Prediction Using Soft Computing Approach
One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes.
Xiaosheng Wang, Osamu Gotoh
doaj +2 more sources
An intracellular transporter mitigates the CO2‐induced decline in iron content in Arabidopsis shoots
This study identifies a gene encoding a transmembrane protein, MIC, which contributes to the reduction of shoot Fe content observed in plants under elevated CO2. MIC is a putative Fe transporter localized to the Golgi and endosomal compartments. Its post‐translational regulation in roots may represent a potential target for improving plant nutrition ...
Timothy Mozzanino +7 more
wiley +1 more source
Background Accurate structural annotation depends on well-trained gene prediction programs. Training data for gene prediction programs are often chosen randomly from a subset of high-quality genes that ideally represent the variation found within a ...
Megan J. Bowman +3 more
doaj +1 more source
In recent years, drug sensitivity prediction has garnered a great deal of attention due to the growing interest in precision medicine. Several computational methods have been developed for drug sensitivity prediction and the identification of related ...
Heewon Park +3 more
doaj +1 more source
By dawn or dusk—how circadian timing rewrites bacterial infection outcomes
The circadian clock shapes immune function, yet its influence on infection outcomes is only beginning to be understood. This review highlights how circadian timing alters host responses to the bacterial pathogens Salmonella enterica, Listeria monocytogenes, and Streptococcus pneumoniae revealing that the effectiveness of immune defense depends not only
Devons Mo +2 more
wiley +1 more source

