Expanding biochemical knowledge and illuminating metabolic dark matter with ATLASx

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Image classification has significantly improved using deep learning. This is mainly due to convolutional neural networks (CNNs) that are capable of learning rich feature extractors from large datasets. However, most deep learning classification methods are ...

It was recently demonstrated that nonpersistent radicals can be generated in frozen solutions of metabolites such as pyruvate by irradiation with UV light, enabling radical-free dissolution dynamic nuclear polarization. Although pyruvate is endogenous, the ...

Modelling and analysis of biological systems is crucial in order to quantitatively explain and predict their behaviour. The importance of modelling in systems biology becomes even more evident when tackling complex, large systems. Approaches that rely on ...

Neuroscience incorporates knowledge from a range of scales, from single molecules to brain wide neural networks. Modeling is a valuable tool in understanding processes at a single scale or the interactions between two adjacent scales and researchers use a ...

The advancements in genome editing techniques over the past years have rekindled interest in rational metabolic engineering strategies. While Metabolic Control Analysis (MCA) is a well-established method for quantifying the effects of metabolic engineering ...

Nuclear receptors play pleiotropic roles in cell differentiation, development, proliferation, and metabolic processes to govern liver physiology and pathology. The nuclear receptor, liver receptor homolog-1 (LRH-1, NR5A2), originally identified in the live ...

Motivation: Finding biosynthetic pathways is essential for metabolic engineering of organisms to produce chemicals, biodegradation prediction of pollutants and drugs, and for the elucidation of bioproduction pathways of secondary metabolites. A key step in ...

Background Significant efforts have been made in building large-scale kinetic models of cellular metabolism in the past two decades. However, most kinetic models published to date, remain focused around central carbon pathways or are built around ad hoc re ...

Cancer is a leading cause of death in the world, and the mechanisms that underlie this disease are still not completely understood. As cancer develops and progresses, cells undergo a diversity of mutations that sustain their rapid proliferation and the eva ...

Expanding biochemical knowledge and illuminating metabolic dark matter with ATLASx

Chattez avec Graph Search

Fidelity Estimation Improves Noisy-Image Classification with Pretrained Networks

Radical-free hyperpolarized MRI using endogenously occurring pyruvate analogues and UV-induced nonpersistent radicals

Modelling the Intracellular Environment under Uncertainty, from Post-translational Modification to Metabolic Networks

A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

Constraint-based metabolic control analysis for rational strain engineering

Emerging functions of the nuclear receptor LRH-1 in liver physiology and pathology

NICEpath: Finding metabolic pathways in large networks through atom-conserving substrate-product pairs

The effects of model complexity and size on metabolic flux distribution and control: case study in Escherichia coli

Modeling metabolic and signaling pathways in cancer cells