Qin Ma

IRIS-DGE is a server-based tool for differential gene expression analysis that integrates multiple R-based methods and provides interactive visualizations for RNA-seq data.

This paper introduces a bi-clustering framework to characterize colorectal cancer subtypes and identify prognostic markers and drug resistance mechanisms beyond CMS classification.

QUBIC2 improves biclustering for bulk and single-cell RNA-Seq by addressing sparsity and transcriptional regulation, outperforming existing tools in functional module detection and cell type classification.

ViDGER provides visualization tools to interpret DGE results from RNA-seq data using Cuffdiff, DESeq2, and edgeR.

This study introduces RECTA, a computational pipeline for regulon prediction in Lactococcus lactis, identifying 51 regulons and validating 14 with acid stress response relevance.

GeneQC estimates the reliability of gene expression levels from RNA-Seq data by analyzing mapping uncertainty, improving downstream analysis validity.

The paper studies chromosomal evolution in cancer cell lines, finding that cells lose sex chromosomes and gain autosomes, leading to a 2:3 X:A ratio that may enhance fitness.

The paper introduces a probabilistic bi-clustering method for single-cell transcriptomic data to detect sub-populations with shared or distinct expression patterns.