AIMC Topic: Metabolome

Clear Filters Showing 91 to 100 of 128 articles

A directed learning strategy integrating multiple omic data improves genomic prediction.

Plant biotechnology journal
Genomic prediction (GP) aims to construct a statistical model for predicting phenotypes using genome-wide markers and is a promising strategy for accelerating molecular plant breeding. However, current progress of phenotype prediction using genomic d...

Architectures and accuracy of artificial neural network for disease classification from omics data.

BMC genomics
BACKGROUND: Deep learning has made tremendous successes in numerous artificial intelligence applications and is unsurprisingly penetrating into various biomedical domains. High-throughput omics data in the form of molecular profile matrices, such as ...

UHPLC-MS/MS method for simultaneous determination of carbamazepine and its seven major metabolites in serum of epileptic patients.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
Carbamazepine (CBZ) was considered as the drug of choice in the treatment for various forms of epilepsy, yet the non-negligible adverse effects of CBZ suspend as the major concern for rational and efficient clinical medication. This study developed a...

Bounded Fuzzy Possibilistic Method Reveals Information about Lung Cancer through Analysis of Metabolomics.

IEEE/ACM transactions on computational biology and bioinformatics
Learning methods, such as conventional clustering and classification, have been applied in diagnosing diseases to categorize samples based on their features. Going beyond clustering samples, membership degrees represent to what degree each sample bel...

A metabolomics-based approach for non-invasive screening of fetal central nervous system anomalies.

Metabolomics : Official journal of the Metabolomic Society
BACKGROUND: Central nervous system anomalies represent a wide range of congenital birth defects, with an incidence of approximately 1% of all births. They are currently diagnosed using ultrasound evaluation. However, there is strong need for a more a...

Application of kernel principal component analysis and computational machine learning to exploration of metabolites strongly associated with diet.

Scientific reports
Computer-based technological innovation provides advancements in sophisticated and diverse analytical instruments, enabling massive amounts of data collection with relative ease. This is accompanied by a fast-growing demand for technological progress...

Exhaled breath condensate metabolome clusters for endotype discovery in asthma.

Journal of translational medicine
BACKGROUND: Asthma is a complex, heterogeneous disorder with similar presenting symptoms but with varying underlying pathologies. Exhaled breath condensate (EBC) is a relatively unexplored matrix which reflects the signatures of respiratory epitheliu...

Predicting novel substrates for enzymes with minimal experimental effort with active learning.

Metabolic engineering
Enzymatic substrate promiscuity is more ubiquitous than previously thought, with significant consequences for understanding metabolism and its application to biocatalysis. This realization has given rise to the need for efficient characterization of ...

Machine learning-enabled non-targeted metabolomics reveals nutritional and metabolic responses of Brachypodium distachyon to drought and elevated CO2.

Journal of experimental botany
Rising atmospheric CO2 and intensified drought are reshaping nutrient dynamics in C3 plants, with implications for ecosystem function and food security. To investigate how these stressors jointly affect nutrient homeostasis, we examined Brachypodium ...