diffusion model

Generative Models for Prediction of Non-B DNA Structures

The paper evaluates generative models for improving non-B DNA structure prediction through data augmentation, finding diffusion models perform best for Z-DNA and H-DNA while WGAN excels for G-quadruplexes.

Natural Language Prompts Guide the Design of Novel Functional Protein Sequences

This paper introduces BioM3, a framework that uses natural language prompts to design functional proteins, achieving state-of-the-art performance in prediction and generating proteins with native-like structures and function.

Generating Multi-state Conformations of P-type ATPases with a Diffusion Model

The paper introduces a diffusion model to generate diverse conformations of P-type ATPases, demonstrating high accuracy in capturing functional states.

BrainACTIV: Identifying visuo-semantic properties driving cortical selectivity using diffusion-based image manipulation

BrainACTIV uses diffusion models to manipulate images and control neural activity in specific brain regions, identifying visuo-semantic properties that drive cortical selectivity.

Diffusion-based artificial genomes and their usefulness for local ancestry inference

This study introduces a frugal diffusion model for generating artificial genomes and evaluates its utility for local ancestry inference using synthetic and real data.

An adaptive autoregressive diffusion approach to design active humanized antibody and nanobody

This paper introduces HuDiff, a diffusion model for humanizing antibodies and nanobodies, showing improved similarity to experimentally humanized sequences and enhanced binding affinity.

CELL-Diff: Unified diffusion modeling for protein sequences and microscopy images

CELL-Diff generates protein images from sequences and vice versa, outperforming existing methods in fidelity.

HiCDiffusion - diffusion-enhanced, transformer-based prediction of chromatin interactions from DNA sequences

The paper introduces HiCDiffusion, a diffusion model that improves Hi-C matrix prediction by integrating an encoder-decoder architecture, achieving higher resolution and better resemblance to experimental data.

From Noise to Knowledge: Diffusion Probabilistic Model-Based Neural Inference of Gene Regulatory Networks

This paper introduces RegDiffusion, a diffusion model for gene regulatory network inference, showing superior performance on single-cell datasets.

A diffusion model conditioned on compound bioactivity profiles for predicting high-content images

This paper introduces a diffusion model that predicts high-content images based on compound bioactivity profiles, showing improved performance for chemically dissimilar compounds.

Chai-1: Decoding the molecular interactions of life

Chai-1 matches AlphaFold3 on PoseBusters ligand poses (77% vs 76%), beats AlphaFold-Multimer 2.3 on low-homology interfaces, and stays competitive without MSAs on multimers and antibodies.

Exploring Log-Likelihood Scores for Ranking Antibody Sequence Designs

The paper benchmarks generative models for antibody sequence design using log-likelihood scores and finds they correlate with binding affinities, suggesting their potential for ranking.

Accurate Conformation Sampling via Protein Structural Diffusion

UFConf improves protein conformation sampling using a diffusion model based on amino acid sequences, outperforming existing methods and showing utility in drug discovery.

Generative machine learning of ADAR substrates for precise and efficient RNA editing

This paper develops DeepREAD, a generative model for designing ADAR guide RNAs to enable efficient and specific RNA editing for therapeutic applications.

ProT-Diff: A Modularized and Efficient Approach to De Novo Generation of Antimicrobial Peptide Sequences through Integration of Protein Language Model and Diffusion Model

ProT-Diff generates novel antimicrobial peptides using a protein language model and diffusion model, producing 34 active peptides against bacteria with low toxicity.

AptaDiff: de novo design and optimization of aptamers based on diffusion models

AptaDiff generates and optimizes aptamers using diffusion models, outperforming existing methods and experimental candidates in binding affinity.

Improving Structural Plausibility in 3D Molecule Generation via Property-Conditioned Training with Distorted Molecules

The paper improves 3D molecule generation by conditioning diffusion models on distorted molecules to enhance structural plausibility and validity.

Parasitic and Commensal interactions among Mimiviruses, Sputnik-like virophages, and Transpovirons: A theoretical and dynamical systems approach.

The paper develops a dynamical systems model to study interactions among Mimiviruses, virophages, and transpovirons, finding oscillatory behavior but unclear biological mechanisms for transpoviron persistence.

Guiding diffusion models for antibody sequence and structure co-design with developability properties

This paper designs antibody sequences and structures using a diffusion model guided by developability properties like solubility and folding stability.

Diffusion Wavelets on Connectome: Localizing the Sources of Diffusion Mediating Structure-Function Mapping Using Graph Diffusion Wavelets

The paper introduces graph diffusion wavelets to estimate functional connectivity from structural connectivity, achieving high correlation and revealing power-law diffusion scales and frontal pole dominance.

Generating realistic neurophysiological time series with denoising diffusion probabilistic models

This paper uses denoising diffusion probabilistic models to generate realistic neurophysiological time series, capturing both general and dataset-specific features across multiple species and recording modalities.

Latent Diffusion For Conditional Generation of Molecules

This paper introduces COATI-LDM, a latent diffusion model for generating drug-like small molecules with desired properties, showing improved control and diversity over existing methods.

A design principle of slow-wave sleep firing pattern with Na+ dynamics

The paper introduces a revised neuronal model incorporating Na+ dynamics to explain slow-wave sleep firing patterns and their transition mechanisms.

Counterfactual MRI Generation with Denoising Diffusion Models for Interpretable Alzheimer's Disease Effect Detection

The paper uses diffusion models to generate synthetic MRI scans for Alzheimer's disease effect detection, improving classifier performance with limited real data.

Enhancing Hi-C contact matrices for loop detection with Capricorn, a multi-view diffusion model

Capricorn enhances low-coverage Hi-C contact matrices using a multi-view diffusion model to improve loop detection accuracy across cell lines and chromosomes.

Deep learning of protein energy landscape and conformational dynamics from experimental structures in PDB

This study develops DeepConformer, a diffusion model that learns protein conformational dynamics and energy landscapes from PDB structures and coevolution data, reproducing MD simulation results without using MD data.

PepFlow: direct conformational sampling from peptide energy landscapes through hypernetwork-conditioned diffusion

PepFlow samples peptide conformations using a diffusion-based Boltzmann generator with hypernetworks, achieving faster and accurate predictions than traditional methods.

Designing DNA With Tunable Regulatory Activity Using Discrete Diffusion

This paper introduces D3, a generative model for designing regulatory DNA with tunable activity, showing improved performance over baselines in sequence generation and activity prediction.

HiCDiff: single-cell Hi-C data denoising with diffusion models

HiCDiff denoises single-cell Hi-C data using diffusion models, outperforming existing methods and working well on bulk Hi-C data.

SpatialDiffusion: Predicting Spatial Transcriptomics with DenoisingDiffusion Probabilistic Models

This paper introduces a denoising diffusion model to predict and interpolate spatial transcriptomics data, enabling generative modeling of tissue slices.