Christian Daniel Fankhauser

Convergent network effects along the axis of gene expression during prostate cancer progression

The paper investigates how genomic alterations affect molecular networks in prostate cancer by integrating genomic, transcriptomic, and proteomic data from 105 samples, identifying a sub-network predictive of tumor aggressiveness and recurrence.

Automated Gleason grading of prostate cancer tissue microarrays via deep learning

This study develops a deep learning model to automate Gleason grading of prostate cancer tissue microarrays, achieving agreement with pathologists and expert-level patient stratification.

Multi-region proteome analysis quantifies spatial heterogeneity of prostate tissue biomarkers

This study quantifies spatial proteome heterogeneity in prostate tissues using multi-region analysis and identifies biomarker variability across benign and malignant tissues.