Thilde Terkelsen

This paper introduces a deep generative model to perform differential gene expression analysis on single cancer samples without control samples, outperforming DESeq2 in detecting differentially expressed genes.

MutateX automates in-silico saturation mutagenesis to predict free energy changes of protein mutations, supporting analysis of disease-associated mutations and protein design.

CAMPP is an open-source R pipeline that simplifies high-throughput data analysis for non-experts, providing tools for normalization, clustering, differential expression, and biomarker prediction.

The paper analyzes the transcriptomic, mutational, and structural alterations of pro-survival Bcl-2 proteins in breast cancer to identify potential therapeutic targets.

The paper analyzes RNA-Seq data from lung cancer subtypes to identify molecular signatures and immune-related features associated with LUAD and LUSC.

Moonlight identifies cancer driver genes and their roles by integrating functional analysis and gene regulatory networks from expression data, distinguishing tumor suppressors, oncogenes, and moonlight genes.