AIMC Topic: Lipids
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A machine learning approach to estimation of phase diagrams for three-component lipid mixtures.
Biochimica et biophysica acta. Biomembranes
May 11, 2020
The plasma membrane of eukaryotic cells is commonly believed to contain ordered lipid domains. The interest in understanding the origin of such domains has led to extensive studies on the phase behavior of mixed lipid systems. Three-component phase d...
Target Identification Using Homopharma and Network-Based Methods for Predicting Compounds Against Dengue Virus-Infected Cells.
Molecules (Basel, Switzerland)
Apr 18, 2020
Drug target prediction is an important method for drug discovery and design, can disclose the potential inhibitory effect of active compounds, and is particularly relevant to many diseases that have the potential to kill, such as dengue, but lack any...
Improving lipid mapping in Genome Scale Metabolic Networks using ontologies.
Metabolomics : Official journal of the Metabolomic Society
Mar 25, 2020
INTRODUCTION: To interpret metabolomic and lipidomic profiles, it is necessary to identify the metabolic reactions that connect the measured molecules. This can be achieved by putting them in the context of genome-scale metabolic network reconstructi...
Using isotopic envelopes and neural decision tree-based in silico fractionation for biomolecule classification.
Analytica chimica acta
Feb 20, 2020
Untargeted mass spectrometry (MS) workflows are more suitable than targeted workflows for high throughput characterization of complex biological samples. However, analysis workflows for untargeted methods are inadequate for characterization of comple...
Virtual genetic diagnosis for familial hypercholesterolemia powered by machine learning.
European journal of preventive cardiology
Feb 4, 2020
AIMS: Familial hypercholesterolemia (FH) is the most common genetic disorder of lipid metabolism. The gold standard for FH diagnosis is genetic testing, available, however, only in selected university hospitals. Clinical scores - for example, the Dut...
Systematic Modeling of log Based on Ensemble Machine Learning, Group Contribution, and Matched Molecular Pair Analysis.
Journal of chemical information and modeling
Jan 10, 2020
Lipophilicity, as evaluated by the -octanol/buffer solution distribution coefficient at pH = 7.4 (log ), is a major determinant of various absorption, distribution, metabolism, elimination, and toxicology (ADMET) parameters of drug candidates. In thi...
Nutritional and technological properties of a quinoa (Chenopodium quinoa Willd.) spray-dried powdered extract.
Food research international (Ottawa, Ont.)
Dec 7, 2019
The relevance of an appropriate nutrition requires innovation in the design of food ingredients. The goal of this work was to obtain a powdered extract of quinoa by using spray-drying. To this aim, quinoa flour was suspended in water to obtain a solu...
Non-invasive diagnosis of non-alcoholic steatohepatitis and fibrosis with the use of omics and supervised learning: A proof of concept study.
Metabolism: clinical and experimental
Nov 9, 2019
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) affects 25-30% of the general population and is characterized by the presence of non-alcoholic fatty liver (NAFL) that can progress to non-alcoholic steatohepatitis (NASH), liver fibrosis and cirr...
Unsupervised Machine Learning for Analysis of Phase Separation in Ternary Lipid Mixture.
Journal of chemical theory and computation
Oct 7, 2019
Phase separation in mixed lipid systems has been extensively studied both experimentally and theoretically because of its biological importance. A detailed description of such complex systems undoubtedly requires novel mathematical frameworks that ar...
Using flow cytometry and multistage machine learning to discover label-free signatures of algal lipid accumulation.
Physical biology
Jul 22, 2019
Most applications of flow cytometry or cell sorting rely on the conjugation of fluorescent dyes to specific biomarkers. However, labeled biomarkers are not always available, they can be costly, and they may disrupt natural cell behavior. Label-free q...
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