Joana P. Gonçalves

SigDyn analyzes single-cell mutational signature dynamics to uncover tumor evolution and heterogeneity, revealing therapeutic insights in invasive ductal carcinoma and laryngeal squamous cell carcinoma.

MUSICiAn identifies DNA repair genes by analyzing mutational spectra from CRISPR-Cas9 perturbations without controls, revealing known genes and novel candidates.

The paper uses CRISPR mutational spectra to identify functional roles of genes in DNA repair pathways by analyzing mutational signatures with non-negative matrix factorization.

This paper introduces a multimodal pipeline for spatiomolecular analysis of tissue samples, demonstrating its application in Alzheimer's disease and type 2 diabetes.

X-CRISP predicts CRISPR repair outcomes with domain adaptability and interpretability, outperforming existing models and improving with transfer learning across cell lines.

The paper introduces SNMF, a supervised method to learn mutational signatures and predict DNA repair deficiencies, achieving high accuracy in cell lines and predicting DDR status in tumors.

The paper defines the chromatin landscape of healthy and injured kidney cells using multi-omics data, identifying regulatory elements and transcription factor networks involved in injury response.

ELISL improves synthetic lethality prediction in cancer by integrating context-specific and context-free data, showing better performance and robustness across 8 cancer types.

The paper identifies an epigenetic signature in rhesus macaques linked to innate fear responses and shows its association with human acoustic startle responses.