Dr. J.S. (Joana) de Pinho Gonçalves
Dr. J.S. (Joana) de Pinho Gonçalves
Profiel
Short bio
Website: goncalveslab.tudelft.nl I am an Assistant Professor in Computer Science at the Delft University of Technology (TUDelft). My lab does research on Computational Molecular Biomedicine. Our focus is on on pattern recognition and machine learning approaches to understand gene regulation, uncover disruptions involved in complex disease (especially cancer), identify diagnostic signatures, and predict novel therapeutic targets. We are also interested in addressing fundamental challenges in machine learning that arise in our application domain, such as learning from few or biased samples, jointly learning from labelled and unlabelled data, or learning from multimodal data. Our lab has strong collaborations with leading experimental labs at medical centres in the Netherlands and abroad. Previously, I was a postdoc in computational cancer biology with Lodewyk Wessels at the TU Delft and the Netherlands Cancer Institute (NKI). Before that, I was a Marie Curie/ERCIM postdoctoral fellow in algorithmic computational biology with Gunnar Klau at the Netherlands Research Centre for Mathematics and Informatics (CWI). I did a PhD in computer science with Sara Madeira at the Technical University of Lisbon, and also spent just over a year in the bioinformatics lab of Yves Moreau at the University of Leuven.
Publicaties
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2025-1-28
MUSICiAn: Genome-wide Identification of Genes Involved in DNA Repair via Control-Free Mutational Spectra Analysis
C.F. Seale / Marco Barazas / Robin van Schendel / Marcel Tijsterman / Joana P. Gonçalves
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2025-2-8
X-CRISP: Domain-Adaptable and Interpretable CRISPR Repair Outcome Prediction
C.F. Seale / Joana P. Gonçalves
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2024
Correction to
Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP) (Nature Cell Biology, (2023), 25, 8, (1089-1100), 10.1038/s41556-023-01194-w)
Sanjay Jain / Liming Pei / Joana P. Gonçalves / Huiping Liu / Paul Robson / Raf Van de Plas / Roy Lardenoije / Lukasz G. Migas / Roger Moens / More Authors -
2024-10-8
DCAST: Diverse Class-Aware Self-Training Mitigates Selection Bias for Fairer Learning
Y.I. Tepeli / Joana P. Gonçalves
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2024-11-27
Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning
Y.I. Tepeli / M.J. de Wolf / Joana P. Gonçalves
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