Meng Wang

AMULETY: A Python package to embed adaptive immune receptor sequences

AMULETY generates language model embeddings for adaptive immune receptor sequences using pre-trained models, enabling users to leverage different models for downstream applications.

Supervised fine-tuning of pre-trained antibody language models improves antigen specificity prediction

This study improves antigen specificity prediction by fine-tuning pre-trained antibody language models on SARS-CoV-2 and influenza antigens, showing better accuracy than models trained on embeddings alone.

Language model-based B cell receptor sequence embeddings can effectively encode receptor specificity

This study evaluates B cell receptor sequence embeddings for predicting sequence properties and specificity, finding that BCR-specific embeddings and paired-chain sequences improve performance.

A computational solution for bolstering reliability of epigenetic clocks: Implications for clinical trials and longitudinal tracking

This paper introduces a computational method to improve the reliability of epigenetic clocks by using principal component analysis, showing reduced technical noise and better performance in longitudinal studies.

Connectome: computation and visualization of cell-cell signaling topologies in single-cell systems data

Connectome quantifies and visualizes cell-cell signaling networks from single-cell RNA-sequencing data using a software package for R.

A rat epigenetic clock recapitulates phenotypic aging and co-localizes with heterochromatin-associated histone modifications

This paper develops a rat epigenetic clock (DNAmAge) that correlates with age and phenotypic aging, and identifies histone modifications linked to its signal.