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Design Of Ultrabright Biosensor For Dynamic Kinase Imaging

Brief description not available

TransPPGSep: Fetal Signal Separation using Physically and Physiologically Compliant Synthetic Data

Researchers at the University of California, Davis have developed a machine learning system for accurately separating fetal signals from mixed maternal-fetal photoplethysmography signals acquired non-invasively to enable fetal physiological parameter monitoring.

Polymeric Benzopyrylium Chemistries for Peroxynitrite Detection in Disease

Brief description not available

Advanced Biocatalytic Methods for the Synthesis of Non-Canonical Amino Acids and Amine Derivatives

Brief description not available

PEINT (Protein Evolution IN Time)

UC Berkeley researchers have developed a sophisticated computer-implemented framework that leverages transformer architectures to model the evolution of biological sequences over time. Unlike traditional phylogenetic models that often assume sites evolve independently, this framework utilizes a coupled encoder-decoder transformer to parameterize the conditional probability of a target sequence given multiple unaligned sequences. By capturing complex interactions and dependencies across different sites within a protein or genomic sequence, the model estimates the transition likelihood for each position. This estimation allows for a high-fidelity simulation of evolutionary trajectories. This approach enables a deeper understanding of how proteins change across different timescales and environmental pressures.

Automated Critical Congenital Heart Disease Screening Combining Non-Invasive Measurements of Oxygenation and Perfusion

Researchers at the University of California, Davis have developed a computer-implemented method for accurately classifying congenital heart defects in newborns using pulse oximetry and machine learning.

A Silicon Microneedle Array Atmospheric Pressure Plasma Ionization Source for Real-Time Trace Gas Chemical Analysis

Researchers at the University of California, Davis have developed an atmospheric pressure ionization source that employs an ordered array of micro-needles designed to ionize sample components.

Host-Based Intrusion Detection Systems Powered By Large Language Models

SHIELD leverages a customized large language model pipeline to detect and investigate sophisticated cyber threats with high accuracy and interpretability.