Chen Li

Modification-aware AI enables terminal chemical modifications for peptide design and discovers potent antimicrobials

This study introduces Termini, an AI framework for designing antimicrobial peptides with terminal modifications, achieving high hit rates and therapeutic potential in vitro and in vivo.

Immunopeptidomics reveals peptide antigens preferentially presented in psoriasis lesional skin of HLA-C*06:02 carriers

The paper identifies HLA-C*06:02-presented peptides in psoriasis lesions, finding lesion-specific peptides linked to disease pathogenesis.

Rethinking Representation Complexity in Drug-Target Prediction via Supervised Vector Quantization

This study evaluates complex features in drug-target interaction prediction and introduces a supervised vector quantization framework that improves performance and interpretability.

A transgenic mouse allows to capture the HLA-C*06:02 immunopeptidome in a model of psoriasis

The paper presents a comprehensive HLA-C*06:02 immunopeptidome dataset from psoriasis-relevant cell lines and psoriasiform skin using a transgenic mouse model.

Delineation of signaling routes that underlie differences in macrophage phenotypic states

This study identifies key kinases and transcription factors regulating immunosuppressive macrophages and validates proteomic signatures for detecting pro-inflammatory macrophages in tumors.

scRCA: a Siamese network-based pipeline for the annotation of cell types using imperfect single-cell RNA-seq reference data

scRCA improves cell type annotation using noisy reference data by combining a Siamese network with noise-robust loss functions and outperforms existing methods.

MERITS: a web-based integrated MycobacterialPE/PPE protein database

MERITS provides a comprehensive database of PE/PPE proteins from Mycobacterium, offering structural and functional information to aid in vaccine and diagnostic development.

TCR_Explore: a novel webtool for T cell receptor repertoire analysis

TCR_Explore is a webtool for TCR repertoire analysis that automates quality control and analysis, enabling non-expert users to generate publication-ready figures.

Towards a systematic characterization of protein complex function: a natural language processing and machine-learning framework

PCfun annotates protein complex function using natural language processing and machine learning, integrating word embeddings from PubMed Central articles with supervised and unsupervised methods.

Immunopeptidomics for Dummies: Detailed Experimental Protocols and Rapid, User-Friendly Visualization of MHC I and II Ligand Datasets with MhcVizPipe

The paper provides detailed experimental protocols and an open-source tool, MhcVizPipe, for analyzing MHC I and II ligand datasets in immunopeptidomics.

Systematic protein complex profiling and differential analysis from co-fractionation mass spectrometry data

The paper introduces PCprophet, a computational framework for identifying and analyzing protein complexes from co-fractionation mass spectrometry data across conditions.