Transfer learning for genomic prediction in underrepresented populations
General Science
More from the blog
Researchers improve weather forecasts looking two to six weeks out
A new machine-learning approach broke records for weather forecasting for an important time frame in emergency planning.
Google DeepMind and Singapore Government announce new AI tool to protect citizens against scams
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
How artificial neural networks build their own learning machinery
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
Developing Gemini 4 Argon responsibly and safely
Learn more about our approach to safety and security for Gemini 4 Argon.
Related papers
A Simultaneous, Multidisciplinary Development and Design Journey - Reflections on Prototyping
A wayfaring approach for the early concept creation stage of development projects that have a very high degree of intended innovation and thus uncertainty and the importance of including all the involved disciplines (knowledge domains) from the beginning of the project on.
PepPCBench is a Comprehensive Benchmarking Framework for Protein-Peptide Complex Structure Prediction
PepPCBench enables a robust evaluation of PFNN-based methods and supports their continued development for peptide-protein structure prediction, and highlights the influence of peptide length, conformational flexibility, and training set similarity on prediction accuracy.
DRHIN: An Integrated and Interactive Web Server for Drug Repositioning
The DRHIN platform provides a code-free portal supporting three key predictive tasks: discovering drug-disease associations, repurposing existing drugs for new indications, and identifying potential therapies for specific diseases, making analyses accessible and reproducible.
Engineering RAG Systems for Real-World Applications: Design, Development, and Evaluation
Five domain-specific RAG applications developed for real-world scenarios across governance, cybersecurity, agriculture, industrial research, and medical diagnostics are presented, highlighting technical, operational, and ethical challenges affecting the reliability and usability of RAG systems in practice.