AIMC Topic: Metabolomics
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Cognitive analysis of metabolomics data for systems biology.
Nature protocols
Jan 22, 2021
Cognitive computing is revolutionizing the way big data are processed and integrated, with artificial intelligence (AI) natural language processing (NLP) platforms helping researchers to efficiently search and digest the vast scientific literature. M...
Covid-19 Automated Diagnosis and Risk Assessment through Metabolomics and Machine Learning.
Analytical chemistry
Jan 20, 2021
COVID-19 is still placing a heavy health and financial burden worldwide. Impairment in patient screening and risk management plays a fundamental role on how governments and authorities are directing resources, planning reopening, as well as sanitary ...
Systems biology in cardiovascular disease: a multiomics approach.
Nature reviews. Cardiology
Dec 18, 2020
Omics techniques generate large, multidimensional data that are amenable to analysis by new informatics approaches alongside conventional statistical methods. Systems theories, including network analysis and machine learning, are well placed for anal...
A Customizable Analysis Flow in Integrative Multi-Omics.
Biomolecules
Nov 27, 2020
The number of researchers using multi-omics is growing. Though still expensive, every year it is cheaper to perform multi-omic studies, often exponentially so. In addition to its increasing accessibility, multi-omics reveals a view of systems biology...
A random forest based biomarker discovery and power analysis framework for diagnostics research.
BMC medical genomics
Nov 23, 2020
BACKGROUND: Biomarker identification is one of the major and important goal of functional genomics and translational medicine studies. Large scale -omics data are increasingly being accumulated and can provide vital means for the identification of bi...
Metabolomics of Prostate Cancer Gleason Score in Tumor Tissue and Serum.
Molecular cancer research : MCR
Nov 9, 2020
Gleason score, a measure of prostate tumor differentiation, is the strongest predictor of lethal prostate cancer at the time of diagnosis. Metabolomic profiling of tumor and of patient serum could identify biomarkers of aggressive disease and lead to...
Predictive diagnosis of chronic obstructive pulmonary disease using serum metabolic biomarkers and least-squares support vector machine.
Journal of clinical laboratory analysis
Nov 3, 2020
OBJECTIVE: Development of biofluid-based biomarkers is attractive for the diagnosis of chronic obstructive pulmonary disease (COPD) but still lacking. Thus, here we aimed to identify serum metabolic biomarkers for the diagnosis of COPD.
Big data in severe mental illness: the role of electronic monitoring tools and metabolomics.
Personalized medicine
Oct 30, 2020
There is an increasing interest in the development of effective early detection and intervention strategies in severe mental illness (SMI). Ideally, these efforts should lead to the delineation of accurate staging models of SMI enabling personalized ...
MetaClean: a machine learning-based classifier for reduced false positive peak detection in untargeted LC-MS metabolomics data.
Metabolomics : Official journal of the Metabolomic Society
Oct 21, 2020
INTRODUCTION: Despite the availability of several pre-processing software, poor peak integration remains a prevalent problem in untargeted metabolomics data generated using liquid chromatography high-resolution mass spectrometry (LC-MS). As a result,...
Predicting human health from biofluid-based metabolomics using machine learning.
Scientific reports
Oct 19, 2020
Biofluid-based metabolomics has the potential to provide highly accurate, minimally invasive diagnostics. Metabolomics studies using mass spectrometry typically reduce the high-dimensional data to only a small number of statistically significant feat...
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