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.

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

[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.

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

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

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

PPTStab: Designing of thermostable proteins with a desired melting temperature

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

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

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

Collection of prediction models for biological tasks

[Under Review] Implementation of Recursive Cleaning for Large-scale Protein Data via Multimodal Learning

TooT-PLM-ionCT: A bioinformatics framework utilizing protein language models for accurate classification of ion channels and ion transporters from membrane proteins.

Large language models for predicting ion channels modulating proteins

Assessing the applicability domain of protein language models trained on UniRef clusters using embedding-based similarity metrics