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N-of-one differential gene expression without control samples using a deep generative model

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: an automated pipeline for in-silico saturation mutagenesis of protein structures and structural ensembles

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

CAncer bioMarker Prediction Pipeline (CAMPP) - A standardised and user-friendly framework for the analysis of quantitative biological data.

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.

Alterations of the pro-survival Bcl-2 protein interactome in breast cancer at the transcriptional, mutational and structural level

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

Different molecular signatures in lung cancer types from integrative bioinformatic analyses of RNASeq data

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

Moonlight: a tool for biological interpretation and driver genes discovery

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.