Weicai Long

BioMaster automates complex bioinformatics workflows using a multi-agent system, improving accuracy, efficiency, and scalability across tasks like RNA-seq and Hi-C processing.

ContextTAD improves TAD calling from Hi-C contact maps by learning context-aware boundary evidence, achieving strong performance across multiple evaluation settings.

PopGenAgent streamlines population genetics analyses by organizing tasks into a structured workflow, enabling reproducible and transparent multi-step analyses with preserved intermediate results.

Mut-BPE improves variant effect prediction by enhancing BPE tokenization with single-nucleotide resolution, showing better performance in AUROC and AUPRC across multiple datasets.

NyxBind improves TFBS prediction by using contrastive learning to enhance DNN representations, outperforming existing models across benchmarks.

MutBERT improves genomic foundation models by using a probabilistic representation of SNPs, outperforming existing models on downstream tasks.