Zhengjun Zhang

The paper identifies gene-gene interactions specific to Omicron variants that correlate with high R0 and proposes potential druggable targets for antiviral drugs.

The paper identifies four critical differentially expressed genes in colorectal cancer using transcriptomic data from multiple cohorts and validates their predictive power and potential as druggable/vaccinable targets.

The paper identifies two genes, ATP6V1B2 and IFI27, as critical for predicting SARS-CoV-2 infection with high accuracy using a new classifier, highlighting differences in their functional roles compared to COVID-19 disease.

This paper identifies three genomic signature patterns and seven subtypes of COVID-19 based on gene interactions, achieving 100% accuracy in classification.

This paper identifies four genes with 100% accuracy in classifying breast cancer subtypes using a competing linear factor analysis method, showing robust and precise results across multiple studies.

The paper identifies four critical genes with high accuracy in lung cancer subtypes and functional effects, showing robustness across different cohorts and revealing new biological mechanisms.