Simon S. McDade

Mitochondrial metabolism is a key determinant of chemotherapy sensitivity in Colorectal Cancer

This study identifies mitochondrial metabolism as a key factor in 5-fluorouracil resistance in colorectal cancer and shows that targeting mitochondrial Complex I can enhance chemotherapy effectiveness.

Autonomous computational prioritisation of colorectal cancer vulnerabilities via multi-scale AI swarms

This paper introduces a neuro-symbolic framework that autonomously prioritizes colorectal cancer vulnerabilities using multi-scale AI swarms and clinical data, identifying IGF2 as a predictive biomarker for 5-Fluorouracil sensitivity.

A neural network model delivers a highly prognostic protein signature in cancer stem cells that identifies relapse in stage III colorectal cancer patients.

This paper identifies a five-protein stem cell signature using a deep neural network that predicts relapse in stage III colorectal cancer patients.

High-Resolution Spatial Proteomics Characterises Colorectal Cancer Consensus Molecular Subtypes

This study uses high-resolution spatial proteomics to characterize colorectal cancer consensus molecular subtypes at single-cell resolution, revealing subtype-specific immune and metabolic features.

The Molecular Subtyping Resource (MouSR): a user-friendly tool for rapid biological discovery from human or mouse transcriptional data

MouSR is an open-source tool for rapid transcriptomic analysis of human or mouse data, enabling biological discovery without programming expertise.

Dissecting the DNA binding landscape and gene regulatory network of p63 and p53

The paper identifies p63 binding sites and predicts its gene regulatory network using ChIP-seq data and motif analysis, highlighting potential therapeutic targets in SCC.

ACE: A Workbench using Evolutionary Genetic Algorithms for analysing association in TCGA Data

ACE identifies correlations between clinical and genomic data in TCGA using an evolutionary algorithm for efficient analysis.