Machine Learning Models for Phenotype Prediction from Genotype. - Richard Annan; Letu Qingge; Pei Yang 004 (BIBE, 2023)

A Convolutional Denoising Autoencoder for Protein Scaffold Filling. - Jordan Sturtz; Richard Annan; Binhai Zhu; Xiaowen Liu; Letu Qingge (ISBRA, 2023)

Efficient Federated Learning with Multi-Teacher Knowledge Distillation for COVID-19 Detection. - Richard Annan; Hong Qin 003; Xiaohong Yuan; Kaushik Roy 003; Robert H. Newman; Letu Qingge (BCB, 2024)

Federated Learning for COVID-19 Detection: Optimized Ensemble Weighting and Knowledge Distillation. - Richard Annan; Letu Qingge (BIBM, 2024)

Explainable Convolutional Neural Network for Phenotype Prediction from Genotype. - Maxwell Sam; Richard Annan; Pei Yang 004; Mohd Anwar; Kristen L. Rhinehardt; Letu Qingge (HealthCom, 2024)

Explainable convolutional neural network model provides an alternative genome-wide association perspective on mutations in SARS-CoV-2. - Parisa Hatami; Richard Annan; Luis Urias Miranda; Jane Gorman; Mengjun Xie; Letu Qingge; Hong Qin 003 (CoRR, 2024)

Artificial intelligence in COVID-19 research: A comprehensive survey of innovations, challenges, and future directions. - Richard Annan; Letu Qingge (Comput. Sci. Rev., 2025)

Generative AI Models for the Protein Scaffold Filling Problem. - Letu Qingge; Kushal Badal; Richard Annan; Jordan Sturtz; Xiaowen Liu; Binhai Zhu (J. Comput. Biol., 2025)

A data-driven sliding-window pairwise comparative approach for the estimation of transmission fitness of SARS-CoV-2 variants and construction of the evolution fitness landscape. - Md Jubair Pantho; Richard Annan; Landen Alexander Bauder; Sophia Huang; Letu Qingge; Hong Qin 003 (Quant. Biol., 2025)

Genomic privacy and security in the era of artificial intelligence and quantum computing. - Richard Annan; Justin Noland; Kamaria Perkins; Xiaohong Yuan; Kaushik Roy 003; Letu Qingge (Discov. Comput., 2025)