Results 91 to 100 of about 1,035,049 (261)
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
Data hazards in synthetic biology
Synthetic BiologyAbstract Data science is playing an increasingly important role in the design and analysis of engineered biology. This has been fueled by the development of high-throughput methods like massively parallel reporter assays, data-rich microscopy techniques, computational protein structure prediction and design, and the development of whole ...
Natalie R Zelenka +9 more
openaire +3 more sources
Reconstructing enzyme evolution by protein engineering
FEBS Letters, EarlyView.Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler +2 more
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
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
FEBS Letters, EarlyView.Cancer progression is regulated by the dynamic matrix code of the tumor microenvironment, which influences cellular behavior and disease development. Importantly, matrix remodeling in three‐dimensional cancer models more accurately reflects in vivo conditions compared to conventional two‐dimensional systems.
Sylvia Mangani +3 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
Scalable Generation of Synthetic IoT Network Datasets: A Case Study with Cooja
Future InternetPredicting the behavior of Internet of Things (IoT) networks under irregular topologies and heterogeneous battery conditions remains a significant challenge.
Hrant Khachatrian +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
FEBS Letters, EarlyView.The process of internalization of the Shiga toxin A subunit via formation of a complex with the Shiga toxin B subunit, which specifically binds to the Gb3 receptor. The peptide is designed to act as a carrier of drugs into cancer cells. Here, we explored the potential of peptides derived from the catalytic A subunit of Shiga toxin (STxA) to be drug ...
Giulia Opassi +6 more
wiley +1 more source