AIMC Topic: Metabolomics
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The application of artificial neural networks in metabolomics: a historical perspective.
Metabolomics : Official journal of the Metabolomic Society
Oct 18, 2019
BACKGROUND: Metabolomics data, with its complex covariance structure, is typically modelled by projection-based machine learning (ML) methods such as partial least squares (PLS) regression, which project data into a latent structure. Biological data ...
Towards early monitoring of chemotherapy-induced drug resistance based on single cell metabolomics: Combining single-probe mass spectrometry with machine learning.
Analytica chimica acta
Sep 25, 2019
Despite the presence of methods evaluating drug resistance during chemotherapies, techniques, which allow for monitoring the degree of drug resistance in early chemotherapeutic stage from single cells in their native microenvironment, are still absen...
Metabolomics meets machine learning: Longitudinal metabolite profiling in serum of normal versus overconditioned cows and pathway analysis.
Journal of dairy science
Sep 20, 2019
This study aimed to investigate the differences in the metabolic profiles in serum of dairy cows that were normal or overconditioned when dried off for elucidating the pathophysiological reasons for the increased health disturbances commonly associat...
Deep Neural Networks for Classification of LC-MS Spectral Peaks.
Analytical chemistry
Sep 19, 2019
Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics has emerged as a valuable tool for biological discovery, capable of assaying thousands of diverse chemical entities in a single biospecimen. Processing of nontargeted LC-MS spectral d...
Dynamic Metabolomics for Engineering Biology: Accelerating Learning Cycles for Bioproduction.
Trends in biotechnology
Aug 28, 2019
Metabolomics is a powerful tool to rationally guide the metabolic engineering of synthetic bioproduction pathways. Current reports indicate great potential to further develop metabolomics-directed synthetic bioproduction. Advanced mass metabolomics m...
Understanding mixed environmental exposures using metabolomics via a hierarchical community network model in a cohort of California women in 1960's.
Reproductive toxicology (Elmsford, N.Y.)
Jul 9, 2019
Even though the majority of population studies in environmental health focus on a single factor, environmental exposure in the real world is a mixture of many chemicals. The concept of "exposome" leads to an intellectual framework of measuring many e...
Salivary metabolomics with alternative decision tree-based machine learning methods for breast cancer discrimination.
Breast cancer research and treatment
Jul 8, 2019
PURPOSE: The aim of this study is to explore new salivary biomarkers to discriminate breast cancer patients from healthy controls.
Combined network analysis and machine learning allows the prediction of metabolic pathways from tomato metabolomics data.
Communications biology
Jun 18, 2019
The identification and understanding of metabolic pathways is a key aspect in crop improvement and drug design. The common approach for their detection is based on gene annotation and ontology. Correlation-based network analysis, where metabolites ar...
Ontology-based metabolomics data integration with quality control.
Bioanalysis
Jun 10, 2019
The complications that arise when performing meta-analysis of datasets from multiple metabolomics studies are addressed with computational methods that ensure data quality, completeness of metadata and accurate interpretation across studies. This p...
Predicting Ion Mobility Collision Cross-Sections Using a Deep Neural Network: DeepCCS.
Analytical chemistry
Apr 1, 2019
Untargeted metabolomic measurements using mass spectrometry are a powerful tool for uncovering new small molecules with environmental and biological importance. The small molecule identification step, however, still remains an enormous challenge due ...
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