Antoine M. Snijders

A quantitative proteomics dataset for assessment and prediction of low dose X-ray radiation exposure in mice.

The paper presents two large-scale proteomics datasets from mice exposed to varying X-ray doses and time points, enabling biomarker discovery and machine learning applications for radiation exposure assessment.

Is Protein Quantification and Physical Normalization Always Necessary in Proteomics?

This study investigates whether protein quantification and physical normalization are necessary in proteomics by comparing normalized and unnormalized sample inputs, showing that computational normalization can reduce variability in some cases.

A susceptibility gene signature for ERBB2-driven mammary tumor development and metastasis in Collaborative Cross mice with human translational value

The paper identifies a mouse tumor susceptibility gene signature (mTSGS) that predicts chemotherapy response in ERBB2-driven breast cancer, validated in both mouse models and human datasets.