AIMC Topic: Metabolism
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BiPOm: a rule-based ontology to represent and infer molecule knowledge from a biological process-centered viewpoint.
BMC bioinformatics
Jul 23, 2020
BACKGROUND: Managing and organizing biological knowledge remains a major challenge, due to the complexity of living systems. Recently, systemic representations have been promising in tackling such a challenge at the whole-cell scale. In such represen...
An influent responsive control strategy with machine learning: Q-learning based optimization method for a biological phosphorus removal system.
Chemosphere
Jun 14, 2019
Biological phosphorus removal (BPR) is an economical and sustainable processes for the removal of phosphorus (P) from wastewater, achieved by recirculating activated sludge through anaerobic and aerobic (An/Ae) processes. However, few studies have sy...
Deep-DRM: a computational method for identifying disease-related metabolites based on graph deep learning approaches.
Briefings in bioinformatics
Jul 20, 2021
MOTIVATION: The functional changes of the genes, RNAs and proteins will eventually be reflected in the metabolic level. Increasing number of researchers have researched mechanism, biomarkers and targeted drugs by metabolites. However, compared with o...
Neural networks and robotic microneedles enable autonomous extraction of plant metabolites.
Plant physiology
Jul 6, 2021
Plant metabolites comprise a wide range of extremely important chemicals. In many cases, like savory spices, they combine distinctive functional properties-deterrence against herbivory-with an unmistakable flavor. Others have remarkable therapeutic q...
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