Results 211 to 220 of about 4,311,294 (371)

Multi‐View Biomedical Foundation Models for Molecule‐Target and Property Prediction

open access: yesAdvanced Science, EarlyView.
Molecular foundation models can provide accurate predictions for a large set of downstream tasks. We develop MMELON, an approach that integrates pre‐trained graph, image, and text foundation models and validate our multi‐view model on over 120 tasks, including GPCR binding.
Parthasarathy Suryanarayanan   +17 more
wiley   +1 more source

His‐MMDM: Multi‐Domain and Multi‐Omics Translation of Histopathological Images with Diffusion Models

open access: yesAdvanced Science, EarlyView.
His‐MMDM is a diffusion model‐based framework for scalable multi‐domain and multi‐omics translation of histopathological images, enabling tasks from virtual staining, cross‐tumor knowledge transfer, and omics‐guided image editing. ABSTRACT Generative AI (GenAI) has advanced computational pathology through various image translation models.
Zhongxiao Li   +13 more
wiley   +1 more source

Transcription Factor Promiscuity Drives Regulatory Rewiring and Evolvability in Gene Networks in Bacteria

open access: yesAdvanced Science, EarlyView.
ABSTRACT This special issue marking the University of Bath's 60th anniversary offers an opportunity to reflect on nearly a decade of research into the evolution of gene regulatory networks (GRNs) from members of the lab and elsewhere. Our goal is to understand how GRNs rewire and how new transcription factor (TF) functions evolve. Using an experimental
Tiffany B. Taylor, Alan M. Rice
wiley   +1 more source

Accelerated Discovery of Topological Conductors for Nanoscale Interconnects

open access: yesAdvanced Science, EarlyView.
Copper interconnects exhibit a sharp increase in resistivity at ultra‐scaled dimensions, threatening continued miniaturization of integrated circuits. The gapless surface states of topological semimetals provide conduction channels resistant to localization.
Alexander C. Tyner   +7 more
wiley   +1 more source

High‐Conductivity Electrolytes Screened Using Fragment‐ and Composition‐Aware Deep Learning

open access: yesAdvanced Science, EarlyView.
We present a new deep learning framework that hierarchically links molecular and functional unit attributions to predict electrolyte conductivity. By integrating molecular composition, ratios, and physicochemical descriptors, it achieves accurate, interpretable predictions and large‐scale virtual screening, offering chemically meaningful insights for ...
Xiangwen Wang   +6 more
wiley   +1 more source

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