Catharina Olsen

D2D improves protein mutation effect predictions using evolutionary constraints and a language model, outperforming existing methods in stability, binding, and epistasis.

This study identifies ΔNP63 as a marker for exocrine-committed multipotent progenitors in the murine pancreas, showing its role in exocrine development and differentiation.

A randomized trial compares genome sequencing to standard of care in diagnosing developmental disorders, finding higher diagnostic yield with genome sequencing.

D2Deep predicts cancer driver mutations by combining protein language models and evolutionary information, outperforming existing methods and enabling result interpretation.

This study tracks genetic changes in human pluripotent stem cells over time, finding that recurrent chromosomal gains drive the accumulation of other mutations.

The paper introduces Moonlight2, an updated framework that uses mutation-based mechanistic indicators to identify driver genes in cancer, applied to Basal-like breast cancer.

The paper introduces new features in the TCGAbiolinks R/Bioconductor package to improve cancer data analysis, including better differential expression analysis, tumor purity estimation, and integration of normal samples from GTEx.

TCGAbiolinksGUI provides a graphical interface for analyzing GDC cancer data, making the TCGAbiolinks package more accessible to non-R users.

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.