Yang Liao

DrugEvolve autonomously evolves algorithms across drug development stages, improving performance on benchmark tests and showing generalizability across data modalities.

The paper identifies genes and mechanisms enabling pathogen persistence in freshwater ecosystems using paired in situ and molecular analyses of Escherichia, Klebsiella, and Enterococcus.

This study shows that p53 inactivation promotes breast cancer brain metastasis by altering fatty acid metabolism, with implications for therapeutic targeting.

This study shows DNMT3A mutations reduce DNA methylation and disrupt p53 pathway, increasing self-renewal and cancer risk in hematopoietic cells.

The paper introduces an enAsCas12a mouse model and associated libraries for efficient gene editing and screening, identifying drug resistance genes and enabling simultaneous gene knockouts and activations.

This study identifies IL6/STAT3 signaling as a therapeutic target for TP53-mutant gastric cancer by showing its role in metastatic progression driven by mutant Trp53.

This paper shows that dividing out quantification uncertainty from transcript counts improves differential expression analysis using edgeR.

This study uses human kidney organoids to model hypoxic injury and maladaptive repair, identifying molecular and metabolic changes associated with AKI and CKD progression.

This study compares the impact of Ensembl and RefSeq gene annotations on RNA-seq quantification accuracy using a benchmark dataset and finds RefSeq provides better accuracy but has decreased annotation accuracy due to recent expansion.

This study shows that read trimming is not necessary for accurate RNA-seq gene expression quantification and reduces analysis time.

The paper introduces Rsubread, an R package for RNA-seq alignment and quantification, showing it is faster, cheaper, and more accurate than existing tools.