Nautilus Biotechnology Unveils Voyager Platform, Enabling Single-Molecule Iterative Mapping, at US HUPO 2026

Revealed core proteomics instrument during US HUPO 2026 following successful field evaluation at the Buck Institute for Research on Aging• ...
News-Medical.Net

MULTI-evolve accelerates protein engineering with machine learning

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 possible variants-more combinations than atoms in the observable universe.

Lab-in-the-loop framework enables rapid evolution of complex multi-mutant proteins

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20100 ...
Cyber Defense Magazine

Deepfakes, Synthetic Media, and Digital Trust: The Cybersecurity Implications of Deepfake Technology and Methods for Detection and Mitigation

Introduction The proliferation of deepfake technology, synthetic media generated using advanced artificial intelligence techniques, has emerged as a ...
The Register on MSN

Machine learning could yield faster, cheaper lithium-ion battery development

Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could dramatically slash the cost and energy required to develop new lithium-ion ...
chromatographyonline

A Novel Machine Learning Method for Predicting Retention Time of Small Molecule Pharmaceutical Compounds Across Reversed-phase HPLC Columns

Traditional QSRR models are limited to single-column predictions, hindering adaptability across diverse LC setups in pharmaceutical settings. The new ML-based approach predicts retention times using ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
IEEE

Multi-Task Transfer Learning in Trajectory Tracking Control Problems using Iterative Learning Control

Abstract: Transfer learning in robotics aims to transfer knowledge across different robot agents or tasks. Current methods in trajectory tracking problems leverage transferred knowledge to provide a ...
C&EN

Nontargeted Analysis with Machine Learning Method Revealing New Chlorinated Byproducts of Tire-Leaching Compounds and Their Formation Pathways During Water Chlorination

Division of Analytical and Environmental Toxicology, Department of Laboratory Medicine and Pathology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB T6G 2G3, Canada Division of ...
C&EN

Design of Tau Aggregation Inhibitors Using Iterative Machine Learning and a Polymorph-Specific Brain-Seeded Fibril Amplification Assay

Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, U.K. Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University ...
IEEE

Iterative Learning Predictive Control Method Based on Reinforcement Learning for Rubber Mixing Batch Process

Abstract: As a typical batch production process, the rubber mixing process involves complex dynamics and significant fluctuations in results. Since the mixing temperature is key to product quality, ...