Researchers
| Name | Position | Topic | Project | Collab. | Funding | Year |
|---|---|---|---|---|---|---|
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Head | 2017-present | ||||
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Postdoc | [computational] modelling of single-cell response to proton therapy | PROTON-SINC | Erasmus MC (Chien) | Convergence | 2020-present |
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Postdoc | [experimental] modelling of single-cell response to proton therapy | PROTON-SINC | Erasmus MC (Chien) | Convergence | 2020-present |
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Postdoc (guest) | longitudinal analysis and prediction models epigenetic effects of stress & trauma exposure in rhesus monkeys |
Harvard/Göttingen (Klengel) | 2019-present | ||
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PhD | multimodal machine learning pattern discovery across molecular modalities |
BIOMIC | Vanderbilt University (Spraggins) | NIH HuBMAP | 2021-present |
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PhD | learning paradigms prediction of candidate targets for anticancer therapy |
ONCOTARGETS | INSY/TU Delft | Sep 2020-present | |
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PhD | representation learning mechanisms of proton-induced DNA damage response |
PROTON-DDR | LUMC, Erasmus MC (Tijsterman, Kanaar, Reinders) | HollandPTC | Sep 2020-present |
Thesis Students
| Name | Programme | Topic | Year |
|---|---|---|---|
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MSc Computer Science | Representation learning for CRISPR repair outcome prediction | Starting in 2021 |
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MSc Computer Science + Nanobiology | Integrated learning of signatures and prediction of DNA repair deficiency | Starting in 2021 |
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MSc Nanobiology | Interpretability and explainability of CRISPR outcome prediction models | Starting in 2021 |
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MSc Computer Science | Semi-supervised learning for prediction of synthetic lethality | Starting in 2021 |
|
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MSc Computer Science | Exploring mutational signatures for prediction of synthetic lethality | Starting in 2021 |
Alumni
| Name | Programme | Topic | Year |
|---|---|---|---|
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MSc Computer Science | mutational signatures of CRISPR repair outcomes | 2020-2021 |
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MSc Computer Science | interpretable or explainable time-to-event prediction | 2020-2021 |
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MSc Computer Science (cum laude) | prediction of synthetic lethality in cancer: integration, generalisation, bias |
2019-2020 |
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MSc Computer Science | prediction of DNA repair pathways from DNA scars | 2019-2020 |
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MSc Computer Science (cum laude) | multitask learning of gene essentiality in cancer cell lines | 2018-2019 |
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MSc intern Nanobiology | inference of regulation from variation in single-cell gene expression | 2018-2019 |
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BSc Nanobiology | computational reconstruction of cell lineages based on CRISPR recorders | 2019-2021 |
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BSc Nanobiology | single-cell gene expression prediction in pooled CRISPR screens | 2018-2019 |
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BSc Life Science and Technology | prediction of gene essentiality in cancer cell lines | 2017-2018 |
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BSc Nanobiology | analysis of DNA end structures generated by CRISPR-Cas9 | 2017-2018 |