NingNing Chen

Predicting viral host range for reverse zoonosis surveillance

The paper predicts viral host range using a combination of experimental screening and deep learning to identify potential animal reservoirs for reverse zoonotic transmission.

Breaking the Synthesis Barrier for AI-Designed DNA Libraries

This paper introduces PGLD, an AI method that designs cost-effective DNA libraries for high-throughput experiments by optimizing synthesis-aware stochastic libraries.

Contrastive learning for antibody-antigen sequence-to-specificity prediction

This paper introduces CALM, a model that predicts antibody-antigen binding from sequences using contrastive learning, achieving 7% top-1 retrieval on a test set.

High-throughput cell-free profiling of SARS-CoV-2 RBD variants enables rapid and quantitative in vitro affinity landscape mapping

The paper develops a high-throughput method to profile SARS-CoV-2 RBD variants' affinity against antibodies, generating binding energy landscapes for variant analysis.