AIMC Topic: Diffusion

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Flexible protein-ligand docking with diffusion-based side-chain packing.

Proceedings of the National Academy of Sciences of the United States of America
Understanding protein structure and dynamics is crucial for basic biology and drug design. Conventional methods often provide static conformations that inadequately capture protein flexibility. We present PackDock, a framework that integrates deep le...

Visual language model-assisted spectral CT reconstruction by diffusion and low-rank priors from limited-angle measurements.

Physics in medicine and biology
Spectral computed tomography (CT) is a critical tool in clinical practice, offering capabilities in multi-energy spectrum imaging and material identification. The limited-angle (LA) scanning strategy has attracted attention for its advantages in fast...

Diffusion for Diffusion: A versatile multiphysics fields refinement framework in pollutants transportation.

Water research
Refining coupled multiphysics fields in pollutant transport from sparse measurements is critical for environmental risk assessment and industrial pollution mitigation. However, existing numerical solvers and machine learning architectures exhibit inh...

Predicting PFAS Diffusion Coefficients with Active Learning and Molecular Dynamics.

Environmental science & technology
Per- and polyfluoroalkyl substances (PFAS) are over 14 000 synthetic compounds with exceptional environmental persistence. Used extensively in industrial and consumer applications, PFAS resist degradation and accumulate in environmental media and liv...

Fuel-Free Rolosense: Viral Sensing Using Diffusional Particle Tracking.

ACS sensors
High-sensitivity viral diagnostics typically use PCR to detect and amplify viral nucleic acids which requires fluorescence reporters, enzymatic amplification, specialized equipment and can be time-consuming. In this work, we describe fuel-free (FF) R...

Efficient Generation of Protein and Protein-Protein Complex Dynamics via SE(3)-Parameterized Diffusion Models.

Journal of chemical information and modeling
Protein and protein-protein complex conformations play a critical role in biological functions, while exploring these via traditional molecular dynamics (MD) simulation is computationally expensive. Enhanced sampling methods offer improvements but re...

AGDNGDA: Unraveling Drug-Associated Genes with Adaptive Graph Diffusion Networks.

Journal of chemical information and modeling
Understanding the intricate relationships between genes and drugs is crucial for advancing drug discovery. However, biological experiments aimed at identifying gene-drug associations are typically time-consuming and inefficient, leading to significan...

TDMAR-Net: a frequency-aware tri-domain diffusion network for CT metal artifact reduction.

Physics in medicine and biology
Metal implants and other high-density objects cause significant artifacts in computed tomography (CT) images, hindering clinical diagnosis. Traditional metal artifact reduction methods often leave residual artifacts due to sinogram edges discontinuit...

Res-MoCoDiff: residual-guided diffusion models for motion artifact correction in brain MRI.

Physics in medicine and biology
Motion artifacts (ARTs) in brain magnetic resonance imaging (MRI), mainly from rigid head motion, degrade image quality and hinder downstream applications. Conventional methods to mitigate these ARTs, including repeated acquisitions or motion trackin...

MG-DIFF: A novel molecular graph diffusion model for molecular generation and optimization.

PloS one
Recent advancements in denoising diffusion models have revolutionized image, text, and video generation. Inspired by these achievements, researchers have extended denoising diffusion models to the field of molecule generation. However, existing molec...