Imagen de Portada

Transformer-based toxin-protein interaction analysis prioritizes airborne particulate matter components with potential adverse health effects

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhu, Yan, Wang, Shihao, Han, Yong, Lu, Yao, Qiu, Shulan, Jin, Ling, Li, Xiangdong, Zhang, Weixiong
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Biomolecules
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Variant effects on protein-protein interactions: methods, models and diseases
por: Larsen-Ledet, Sven, et al.
Publicado: (2025)

Integrative modelling of protein-glycan interactions with HADDOCK3
por: Reys, Victor, et al.
Publicado: (2026)

Aptamer-protein interaction prediction model based on transformer
por: Yan, Zhichao, et al.
Publicado: (2025)

De novo design of protein binders targeting the human sweet taste receptor as potential sweet proteins
por: Ding, Saisai, et al.
Publicado: (2026)

In silico bioactivity prediction of proteins interacting with graphene-based nanomaterials guides rational design of biosensor
por: Ye, Jing, et al.
Publicado: (2024)

Computational modeling of RNA-protein binding interactions under an external force
por: Wampler, Danielle, et al.
Publicado: (2026)

Causal knowledge graph analysis identifies adverse drug effects
por: Toonsi, Sumyyah, et al.
Publicado: (2025)

Sequence-based protein-protein interaction prediction and its applications in drug discovery
por: Charih, François, et al.
Publicado: (2025)

Structured Random Binding: a minimal model of protein-protein interactions
por: Zou, Ling-Nan
Publicado: (2025)

Assessing interaction recovery of predicted protein-ligand poses
por: Errington, David, et al.
Publicado: (2024)

Assessment of scoring functions for computational models of protein-protein interfaces
por: Sumner, Jacob, et al.
Publicado: (2024)

Agentic AI platforms for autonomous training and rule induction of human-human and virus-human protein-protein interactions
por: Do, Hung N., et al.
Publicado: (2026)

TopoQA: a topological deep learning-based approach for protein complex structure interface quality assessment
por: Han, Bingqing, et al.
Publicado: (2024)

Effective model of protein--mediated interactions in chromatin
por: Borando, Francesco, et al.
Publicado: (2024)

Learning to engineer protein flexibility
por: Kouba, Petr, et al.
Publicado: (2024)

The standard coil or globule phases cannot describe the denatured state of structured proteins and intrinsically disordered proteins
por: Righini, F., et al.
Publicado: (2025)

Protein-Nucleic Acid Complex Modeling with Frame Averaging Transformer
por: Huang, Tinglin, et al.
Publicado: (2024)

The role of topology on protein thermal stability
por: Especial, João N. C., et al.
Publicado: (2025)

Computational design of intrinsically disordered proteins
por: Tesei, Giulio, et al.
Publicado: (2025)

Kermut: Composite kernel regression for protein variant effects
por: Groth, Peter Mørch, et al.
Publicado: (2024)

Predicting mutational effects on protein binding from folding energy
por: Deng, Arthur, et al.
Publicado: (2025)

Predicting protein folding dynamics using sequence information
por: Galpern, Ezequiel A., et al.
Publicado: (2025)

Multiscale differential geometry learning for protein flexibility analysis
por: Feng, Hongsong, et al.
Publicado: (2024)

Controlled protein synthesis and spatial organisation in microfluidic environments
por: Gaizauskaite, Aukse, et al.
Publicado: (2025)

Inferring protein folding mechanisms from natural sequence diversity
por: Galpern, Ezequiel A., et al.
Publicado: (2024)

A universal phase-plane model for in vivo protein aggregation
por: Cotton, Matthew W., et al.
Publicado: (2025)

From sequence to protein structure and conformational dynamics with AI/ML
por: Ille, Alexander M., et al.
Publicado: (2025)

Fold-switching proteins push the boundaries of conformational ensemble prediction
por: Lee, Myeongsang, et al.
Publicado: (2026)

Physical principles of building protein megacomplexes in a crowded milieu
por: Wang, Jiayi, et al.
Publicado: (2026)

Persistent local Laplacian prediction of protein-ligand binding affinities
por: Liu, Jian, et al.
Publicado: (2026)

Towards deep learning sequence-structure co-generation for protein design
por: Wang, Chentong, et al.
Publicado: (2024)

Training a force field for proteins and small molecules from scratch
por: Blanco-González, Alexandre, et al.
Publicado: (2026)

De novo design of high-affinity protein binders with AlphaProteo
por: Zambaldi, Vinicius, et al.
Publicado: (2024)

Disordered But Rhythmic: the role of intrinsic protein disorder in eukaryotic circadian timing
por: Usher, Emery T., et al.
Publicado: (2025)

ApexGen: Simultaneous design of peptide binder sequence and structure for target proteins
por: Xia, Xiaoqiong, et al.
Publicado: (2025)

Out-of-equilibrium selection pressure enhances inference from protein sequence data
por: Dietler, Nicola, et al.
Publicado: (2026)

AlphaFold2 for protein structure prediction: Best practices and critical analyses
por: Radjasandirane, Ragousandirane, et al.
Publicado: (2024)

Evaluating and Scoring Ebolavirus Protein-protein Docking Models Using PIsToN
por: Shirali, Azam, et al.
Publicado: (2025)

Frontiers in integrative structural biology: modeling disordered proteins and utilizing in situ data
por: Majila, Kartik, et al.
Publicado: (2024)

Machine learning methods to study sequence-ensemble-function relationships in disordered proteins
por: von Bülow, Sören, et al.
Publicado: (2024)