Project: Unravelling cellular heterogeneity and dynamics in normal and malignant hematopoiesis using singlecell bioinformatics
2018-01-01 – 2022-12-31
- Abstract
In this multi-disciplinary project, we will pioneer the development and application of single-cell genomics to study the heterogeneity and dynamics of the immune system.
Our consortium will pioneer the role of single-cell genomics at Ghent University, developing novel bioinformatics approaches to study cell differentiation and dynamics, and combining them with both fundamental research in immunology as well as clinical applications.
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- Journal Article
- A2
- open access
funkyheatmap : visualising data frames with mixed data types
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- Journal Article
- A1
- open access
Unraveling cell-cell communication with NicheNet by inferring active ligands from transcriptomics data
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- Journal Article
- A1
- open access
Unraveling genotype–phenotype associations and predictive modeling of outcome in acute myeloid leukemia
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- Journal Article
- A1
- open access
CytoNorm 2.0 : a flexible normalization framework for cytometry data without requiring dedicated controls
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- Journal Article
- A1
- open access
SpatialData : an open and universal data framework for spatial omics
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- Journal Article
- A1
- open access
A spatial human thymus cell atlas mapped to a continuous tissue axis
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- Journal Article
- A1
- open access
Spotless, a reproducible pipeline for benchmarking cell type deconvolution in spatial transcriptomics
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- Journal Article
- A1
- open access
Efficient cytometry analysis with FlowSOM in Python boosts interoperability with other single-cell tools
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- Miscellaneous
- open access
Defining and benchmarking open problems in single-cell analysis
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- Journal Article
- A1
- open access
Myelodysplastic neoplasms dissected into indolent, leukaemic and unfavourable subtypes by computational clustering of haematopoietic stem and progenitor cells