Results 111 to 120 of about 25,449,411 (299)
Synthetic Data and Health Privacy
JAMAThis Viewpoint discusses generative artificial intelligence and safeguarding privacy by using synthetic data as a substitute for private health data.
Gwénolé Abgrall +2 more
openaire +3 more sources
Prospecting the protein design landscape
FEBS Letters, EarlyView.This review outlines the current state of various protein design approaches. We discuss the current possibilities enabled by recently released tools, highlight future avenues to pursue in protein design, and underscore the crucial role of key databases and resources for successful protein design workflows.
Jakob R. Riccabona +4 more
wiley +1 more source
IEEE AccessSynthetic data offers a compelling solution to the challenges associated with acquiring high-quality medical data, which is often constrained by privacy concerns and limited accessibility.
Abdullah Hosseini, Ahmed Serag
doaj +1 more source
FEBS Letters, EarlyView.Synechocystis strains deficient in succinate dehydrogenase (SDH) secrete more succinate than the WT under dark anaerobic conditions, supporting that SDH then primarily acts as SDH, not as a fumarate reductase. L‐aspartate oxidase (Laspo) from Synechocystis is functional under anaerobic conditions, reducing fumarate to succinate.
Kateryna Kukil +3 more
wiley +1 more source
Computing OpenA speculator in the foreign exchange (Forex) market interacts in an environment where other participants as well as their strategies are unobserved. This constitutes a challenging interaction environment that generates complex time series data that may ...
Patrick Naivasha +3 more
doaj +1 more source
A primer on synthetic health data
CoRRRecent advances in deep generative models have greatly expanded the potential to create realistic synthetic health datasets. These synthetic datasets aim to preserve the characteristics, patterns, and overall scientific conclusions derived from sensitive health datasets without disclosing patient identity or sensitive information.
Jennifer Anne Bartell +4 more
openaire +2 more sources
Artificial molecular machines and motors—Design and control of nanoscale motion
FEBS Letters, EarlyView.Molecules are constantly moving because of thermal fluctuations, but random motion alone cannot be exploited to perform directional tasks. Artificial molecular machines use chemical, electrical, or light energy to bias this motion. Molecular shuttles, rotary motors, and supramolecular pumps illustrate how nanoscale movement can be controlled and ...
Leonardo Andreoni, Alberto Credi
wiley +1 more source
ISPRS International Journal of Geo-InformationThis study explores the impact of synthetic data, both physically based and generatively created, on deep learning analytics for earth observation (EO), focusing on the detection of photovoltaic panels. A YOLOv8 object detection model was trained using a
Enes Hisam +8 more
doaj +1 more source
FEBS Letters, EarlyView.Heterodimeric amino acid transporters consist of SLC7 and SLC3 family proteins arranged in a conserved structural organization. They regulate nutrient transport across cell membranes, supporting essential cellular functions. These transporters also contribute to xenobiotic/drug uptake and distribution.
Mariafrancesca Scalise +5 more
wiley +1 more source
Synthetic pre-training for neural-network interatomic potentials
Machine Learning: Science and TechnologyMachine learning (ML) based interatomic potentials have transformed the field of atomistic materials modelling. However, ML potentials depend critically on the quality and quantity of quantum-mechanical reference data with which they are trained, and ...
John L A Gardner +2 more
doaj +1 more source