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

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

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.

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

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

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

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

PPTStab: Designing of thermostable proteins with a desired melting temperature

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

Coupling codon and protein constraints decouples drivers of variant pathogenicity

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

Protein (language model) Benchmarking Collection - PBC

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

[ICML 2025 Workshop FM4BS] AnnoDPO: Protein Functional Annotation Learning with Direct Preference Optimization

Code for the manuscript "Application of Protein Structure Encodings and Sequence Embeddings for Transporter Substrate Prediction".

Benchmarking antibody-specific PLMs vs. BLOSUM62 for variant fitness prediction on combinatorial CDR-H3 libraries