Natasha Lucas

Federated deep learning enables cancer subtyping by proteomics

ProCanFDL uses federated deep learning to subtype cancers using proteomic data while preserving privacy, achieving performance gains over local models.

Investigating the use of novel blood processing methods to boost the identification of biomarkers of non-small cell lung cancer

This study evaluates novel blood processing methods to identify NSCLC biomarkers, finding 13 proteins with 86.4% accuracy in distinguishing NSCLC patients from controls.

Assessment of a high-throughput mass spectrometry method to accelerate biomarker discovery in clinical cancer cohorts using volumetric absorptive microsampling (VAMS) devices.

The paper evaluates high-throughput mass spectrometry methods using VAMS devices to identify differentially expressed proteins in lung cancer patients and healthy controls, finding 36 discriminatory biomarkers with 88.9% AUC.

Pan-cancer proteomic map of 949 human cell lines reveals principles of cancer vulnerabilities

The paper presents a pan-cancer proteomic map of 949 cell lines, revealing protein-specific biomarkers of cancer vulnerabilities and showing proteomic data's superior predictive power for drug response.