Fenix W. D. Huang

This paper introduces a framework using genomic sequence data to predict the threat of novel SARS-CoV-2 lineages by analyzing co-evolving motifs and evaluates its performance across multiple lineages and countries.

This paper introduces a framework for detecting SARS-CoV-2 variants of interest and concern using co-evolutionary signals in genomic sequences, detecting them weeks earlier than current methods.

tRForest improves tRNA fragment target prediction using random forest, validated in cell lines and showing enrichment in neuronal function.