Results 161 to 170 of about 39,835 (307)

Current Challenges of Transcription Compartmentalization Research

open access: yesAdvanced Science, EarlyView.
Transcription factors, coactivators, and RNA polymerase II assemble into transcription compartments ranging from small, defined complexes to liquid‐like condensates. This review unifies these seemingly competing descriptions along a single continuum and asks what these compartments have been shown to do, and what they have not, revealing that the most ...
Thomas Quail, Sina Wittmann
wiley   +1 more source

Pasta, a Versatile Transcriptomic Clock, Maps the Chemical and Genetic Determinants of Aging and Rejuvenation

open access: yesAdvanced Science, EarlyView.
Pasta is a transcriptomic aging clock built on an age‐shift learning framework and trained on 17 000 samples across 21 datasets. It accurately predicts relative biological age across tissues, platforms, and species, captures stemness‐to‐senescence transitions, and identifies age‐modulatory perturbations.
Jérôme Salignon   +6 more
wiley   +1 more source

Single‐Atom‐Enhanced Fully Inkjet‐Printed Electrochemical Sensor for Dopamine Detection

open access: yesAdvanced Science, EarlyView.
Fully inkjet‐printed paper‐based dopamine sensors are fabricated using nitrogen‐doped graphene acid functionalized with copper single atoms. The copper sites uniquely enhance dopamine oxidation through strong molecular adsorption, as verified by electrochemical measurements and DFT calculations. The approach highlights the potential of single‐atom inks
Martin‐Alex Nalepa   +11 more
wiley   +1 more source

CLRe: A Synergistic Dual‐Engine Framework for One‐Step Retrosynthesis Prediction

open access: yesAdvanced Science, EarlyView.
CLRe uses a contrastive difficulty score to order pretrained seq2seq fine‐tuning for retrosynthesis. Reaction embeddings define the ranking score, and a cumulative easy‐to‐hard schedule expands from the easiest subset to the full training set while earlier examples remain active.
Tianhao Su   +5 more
wiley   +1 more source

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

open access: yesAdvanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali   +3 more
wiley   +1 more source

Home - About - Disclaimer - Privacy