Copertina

PatchProt: Hydrophobic patch prediction using protein foundation models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Gogishvili, Dea, Minois-Genin, Emmanuel, van Eck, Jan, Abeln, Sanne
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Quantitative Methods Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

PLM-eXplain: Divide and Conquer the Protein Embedding Space
di: van Eck, Jan, et al.
Pubblicazione: (2025)

ProtTeX-CC: Activating In-Context Learning in Protein LLM via Two-Stage Instruction Compression
di: Fan, Chuanliu, et al.
Pubblicazione: (2025)

From thermodynamics to protein design: Diffusion models for biomolecule generation towards autonomous protein engineering
di: Li, Wen-ran, et al.
Pubblicazione: (2025)

Generative modeling of protein ensembles guided by crystallographic electron densities
di: Maddipatla, Sai Advaith, et al.
Pubblicazione: (2024)

tcrLM: a lightweight protein language model for predicting T cell receptor and epitope binding specificity
di: Fang, Xing, et al.
Pubblicazione: (2024)

Heterogeneous network drug-target interaction prediction model based on graph wavelet transform and multi-level contrastive learning
di: Dai, Wenfeng, et al.
Pubblicazione: (2025)

Dynamics-inspired Structure Hallucination for Protein-protein Interaction Modeling
di: Wu, Fang, et al.
Pubblicazione: (2026)

PPI-Net connects molecular protein interactions to functional processes in disease
di: Higgins, Kyle, et al.
Pubblicazione: (2026)

The Next Layer: Augmenting Foundation Models with Structure-Preserving and Attention-Guided Learning for Local Patches to Global Context Awareness in Computational Pathology
di: Waqas, Muhammad, et al.
Pubblicazione: (2025)

Pre-trained protein language model for codon optimization
di: Pathak, Shashank, et al.
Pubblicazione: (2024)

Protein binding affinity prediction under multiple substitutions applying eGNNs on Residue and Atomic graphs combined with Language model information: eGRAL
di: Fiorellini-Bernardis, Arturo, et al.
Pubblicazione: (2024)

ProtSAE: Disentangling and Interpreting Protein Language Models via Semantically-Guided Sparse Autoencoders
di: Liu, Xiangyu, et al.
Pubblicazione: (2025)

Machine learning-based multimodal prognostic models integrating pathology images and high-throughput omic data for overall survival prediction in cancer: a systematic review
di: Jennings, Charlotte, et al.
Pubblicazione: (2025)

BMFM-RNA: whole-cell expression decoding improves transcriptomic foundation models
di: Danziger, Michael M., et al.
Pubblicazione: (2025)

Pan-protein Design Learning Enables Task-adaptive Generalization for Low-resource Enzyme Design
di: Zheng, Jiangbin, et al.
Pubblicazione: (2024)

Discovering intrinsic multi-compartment pharmacometric models using Physics Informed Neural Networks
di: Nasim, Imran, et al.
Pubblicazione: (2024)

Point transformer for protein structural heterogeneity analysis using CryoEM
di: Chen, Muyuan, et al.
Pubblicazione: (2026)

Multimodal AI predicts clinical outcomes of drug combinations from preclinical data
di: Huang, Yepeng, et al.
Pubblicazione: (2025)

GraPPI: A Retrieve-Divide-Solve GraphRAG Framework for Large-scale Protein-protein Interaction Exploration
di: Li, Ziwen, et al.
Pubblicazione: (2025)

Assay2Mol: large language model-based drug design using BioAssay context
di: Deng, Yifan, et al.
Pubblicazione: (2025)

SCALE:Scalable Conditional Atlas-Level Endpoint transport for virtual cell perturbation prediction
di: Chen, Shuizhou, et al.
Pubblicazione: (2026)

CaLMFlow: Volterra Flow Matching using Causal Language Models
di: He, Sizhuang, et al.
Pubblicazione: (2024)

Understanding protein function with a multimodal retrieval-augmented foundation model
di: Truong Jr, Timothy Fei, et al.
Pubblicazione: (2025)

LncRNA-disease association prediction method based on heterogeneous information completion and convolutional neural network
di: Xi, Wen-Yu, et al.
Pubblicazione: (2024)

WISER: Weak supervISion and supErvised Representation learning to improve drug response prediction in cancer
di: Shubham, Kumar, et al.
Pubblicazione: (2024)

Surrogate modeling of Cellular-Potts Agent-Based Models as a segmentation task using the U-Net neural network architecture
di: Comlekoglu, Tien, et al.
Pubblicazione: (2025)

ProtSCAPE: Mapping the landscape of protein conformations in molecular dynamics
di: Viswanath, Siddharth, et al.
Pubblicazione: (2024)

EVA: Towards a universal model of the immune system
di: Scienta Team, et al.
Pubblicazione: (2026)

Chemist-aligned retrosynthesis by ensembling diverse inductive bias models
di: Maziarz, Krzysztof, et al.
Pubblicazione: (2024)

Recent advances in deep learning and language models for studying the microbiome
di: Yan, Binghao, et al.
Pubblicazione: (2024)

ProtBoost: protein function prediction with Py-Boost and Graph Neural Networks -- CAFA5 top2 solution
di: Chervov, Alexander, et al.
Pubblicazione: (2024)

AI prediction of cardiovascular events using opportunistic epicardial adipose tissue assessments from CT calcium score
di: Hu, Tao, et al.
Pubblicazione: (2024)

Privacy-Preserving Multi-Center Differential Protein Abundance Analysis with FedProt
di: Burankova, Yuliya, et al.
Pubblicazione: (2024)

Multimodal Integration of Longitudinal Noninvasive Diagnostics for Survival Prediction in Immunotherapy Using Deep Learning
di: Yeghaian, Melda, et al.
Pubblicazione: (2024)

Completion of the DrugMatrix Toxicogenomics Database using 3-Dimensional Tensors
di: Nguyen, Tan, et al.
Pubblicazione: (2025)

Augmenting generative models with biomedical knowledge graphs improves targeted drug discovery
di: Malusare, Aditya, et al.
Pubblicazione: (2025)

Accelerating the inference of string generation-based chemical reaction models for industrial applications
di: Andronov, Mikhail, et al.
Pubblicazione: (2024)

Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learning
di: Adiyeke, Esra, et al.
Pubblicazione: (2025)

A Comprehensive Review of Transformer-based language models for Protein Sequence Analysis and Design
di: Ghosh, Nimisha, et al.
Pubblicazione: (2025)

Deep Learning Model for Amyloidogenicity Prediction using a Pre-trained Protein LLM
di: Yagoub, Zohra, et al.
Pubblicazione: (2025)