protein-language-models

LucaProt: A novel deep learning framework that incorporates protein amino acid sequence and structural information to predict protein function.

Efficient implementatin of ESM family.

Multi-target de novo molecular generator conditioned on AlphaFold's latent protein embeddings.

[AAAI 2025] CoPRA: Bridging Cross-domain Pretrained Sequence Models with Complex Structures for Protein-RNA Binding Affinity Prediction

We developed a dual-channel model named LucaPCycle, based on the raw sequence and protein language large models, to predict whether a protein sequence has phosphate-solubilizing functionality and its specific type among the 31 fine-grained functions.

Nature Computational Science: Unbiased organism-agnostic and highly sensitive signal peptide predictor with deep protein language model

LucaProt: A novel deep learning framework that incorporates protein amino acid sequence and structural information to predict protein function.

PLMFit platform for TL on PLMs

Explore protein language model embeddings in your browser — surface relationships sequence similarity misses, overlay annotations, and transfer labels (EAT). Nothing uploaded.

A book about Language/deep-learning models in Genomics.

Protein Diversification and Generation through Yielded mutations (Prodigy) Protein is an end-to-end platform for plug and play protein engineering

A curated list of protein foundation models, protein language models (pLMs), and generative models for sequence, structure, and multimodal protein modeling.

PPTStab: Designing of thermostable proteins with a desired melting temperature

Source code for "Multimodal out-of-distribution individual uncertainty quantification enhances binding affinity prediction for polypharmacology" (Nature Machine Intelligence)

OTalign: Protein sequence alignment for remote homologs using Protein Language Models and Unbalanced Optimal Transport.

Code, data, and checkpoints for Glydentify, an explainable deep learning platform for glycosyltransferase donor substrate prediction.

Protein (language model) Benchmarking Collection - PBC

Developing classification models for DNA-Binding proteins through machine learning and large language models

Codon-level information complements protein language models for missense variant effect prediction

ESM-2 protein-retrieval failure-mode study with preregistered evidence, calibration analysis, and explicit curation limits.