Results 11 to 20 of about 26,891,998 (226)
Post-Traumatic Epilepsy and Comorbidities: Advanced Models, Molecular Mechanisms, Biomarkers, and Novel Therapeutic Interventions. [PDF]
Pharmacol Rev, 2022 Post-traumatic epilepsy (PTE) is one of the most devastating long-term, network consequences of traumatic brain injury (TBI). There is currently no approved treatment that can prevent onset of spontaneous seizures associated with brain injury, and many ...
Golub VM, Reddy DS.
europepmc +2 more sources
Native or Non-Native Protein-Protein Docking Models? Molecular Dynamics to the Rescue. [PDF]
J Chem Theory Comput, 2021 Molecular docking excels at creating a plethora of potential models of protein-protein complexes. To correctly distinguish the favourable, native-like models from the remaining ones remains, however, a challenge.
Jandova Z, Vargiu AV, Bonvin AMJJ.
europepmc +2 more sources
Rapid Acting Antidepressants in Chronic Stress Models: Molecular and Cellular Mechanisms. [PDF]
Chronic Stress (Thousand Oaks), 2017 Stress-associated disorders, including depression and anxiety, impact nearly 20% of individuals in the United States. The social, health, and economic burden imposed by stress-associated disorders requires in depth research efforts to identify suitable ...
Hare BD, Ghosal S, Duman RS.
europepmc +2 more sources
BMJ, 2016 Many decisions in medicine involve trade-offs, such as between diagnosing patients with disease versus unnecessary additional testing for those who are healthy.
Vickers AJ +2 more
europepmc +2 more sources
Analyzing Learned Molecular Representations for Property Prediction [PDF]
Journal of Chemical Information and Modeling, 2019 Advancements in neural machinery have led to a wide range of algorithmic solutions for molecular property prediction. Two classes of models in particular have yielded promising results: neural networks applied to computed molecular fingerprints or expert-
Kevin Yang +14 more
semanticscholar +4 more sources
Genetic Optimization of Training Sets for Improved Machine Learning Models of Molecular Properties. [PDF]
Journal of Physical Chemistry Letters, 2016 The training of molecular models of quantum mechanical properties based on statistical machine learning requires large data sets which exemplify the map from chemical structure to molecular property. Intelligent a priori selection of training examples is
N. Browning +3 more
semanticscholar +7 more sources
Language models can learn complex molecular distributions [PDF]
Nature Communications, 2021 Deep generative models of molecules have grown immensely in popularity, trained on relevant datasets, these models are used to search through chemical space. The downstream utility of generative models for the inverse design of novel functional compounds,
Daniel Flam-Shepherd +2 more
semanticscholar +1 more source
ADAM10 and ADAM17 regulate EGFR, c-Met and TNF RI signalling in liver regeneration and fibrosis
Scientific Reports, 2021 ADAM10 and ADAM17 are proteases that affect multiple signalling pathways by releasing molecules from the cell surface. As their substrate specificities partially overlaps, we investigated their concurrent role in liver regeneration and fibrosis, using ...
Olga Zbodakova +6 more
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GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation [PDF]
International Conference on Learning Representations, 2022 Predicting molecular conformations from molecular graphs is a fundamental problem in cheminformatics and drug discovery. Recently, significant progress has been achieved with machine learning approaches, especially with deep generative models.
Minkai Xu +5 more
semanticscholar +1 more source
BMC Gastroenterology, 2022 Background Ubiquitin ligases (Ub-ligases) are essential intracellular enzymes responsible for the regulation of proteome homeostasis, signaling pathway crosstalk, cell differentiation and stress responses.
Veronika Iatsiuk +8 more
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