Essays about: "Molecular Property Prediction"
Showing result 1 - 5 of 6 essays containing the words Molecular Property Prediction.
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1. Machine learning for molecular property prediction and drug safety
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : Utilizing machine learning methods for the prediction of acid dissociation (pKa ) values of compounds holds great significance, as pKa is an important parameter, optimized frequently in drug discovery. Accurate prediction of pKa values could potentially provide valuable insights on other molecular properties and thereby support compound design. READ MORE
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2. Sublimation temperature prediction of OLED materials : using machine learning
University essay from Uppsala universitet/Analys och partiella differentialekvationerAbstract : Organic light-emitting diodes (OLED) are and have been the future of display technology for a minute. Looking back, display technology has moved from cathode-ray tube displays (CRTs) to liquid crystal displays (LCDs). Whereas CRT displays were clunky and had quite high powerconsumption, LCDs were thinner, lighter and consumed less energy. READ MORE
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3. Pre-training Molecular Transformers Through Reaction Prediction
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Molecular property prediction has the ability to improve many processes in molecular chemistry industry. One important application is the development of new drugs where molecular property prediction can decrease both the cost and time of finding new drugs. READ MORE
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4. Multi-task regression QSAR/QSPR prediction utilizing text-based Transformer Neural Network and single-task using feature-based models
University essay from Linköpings universitet/Statistik och maskininlärningAbstract : With the recent advantages of machine learning in cheminformatics, the drug discovery process has been accelerated; providing a high impact in the field of medicine and public health. Molecular property and activity prediction are key elements in the early stages of drug discovery by helping prioritize the experiments and reduce the experimental work. READ MORE
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5. Accelerating bulk material property prediction using machine learning potentials for molecular dynamics : predicting physical properties of bulk Aluminium and Silicon
University essay from Linköpings universitet/Teoretisk FysikAbstract : In this project machine learning (ML) interatomic potentials are trained and used in molecular dynamics (MD) simulations to predict the physical properties of total energy, mean squared displacement (MSD) and specific heat capacity for systems of bulk Aluminium and Silicon. The interatomic potentials investigated are potentials trained using the ML models kernel ridge regression (KRR) and moment tensor potentials (MTPs). READ MORE
