S. Gassen

发表

Computational flow cytometry: helping to make sense of high-dimensional immunology data

Y. Saeys, B. Lambrecht, S. Gassen, 2016, Nature Reviews Immunology.

Single-cell molecular profiling using ex vivo functional readouts fuels precision oncology in glioblastoma

Y. Saeys, K. Ligon, M. Tolstorukov, 2022, bioRxiv.

Deep single-cell profiling of the systemic immune response to pregnancy Twenty-one pregnant women receiving routine antepartum care at

R. Tibshirani, G. Nolan, G. Shaw, 2017 .

Presence of Innate Lymphoid Cells in Allogeneic Hematopoietic Grafts Correlates with Reduced Graft-Versus-Host Disease

B. Blom, S. Gassen, C. Voermans, 2022, Transplantation and Cellular Therapy.

Flow cytometry measures multiple parameters of cells that rapidly flow in a stream through a system of photonic detectors. During the past 50 years, flow cytometry has established itself as the workhorse for high-throughput quantitative analysis of cells

Y. Saeys, B. Lambrecht, S. Gassen, 2016 .

Response to Orlova et al. “Science not art: statistically sound methods for identifying subsets in multi-dimensional flow and mass cytometry data sets”

Y. Saeys, B. Lambrecht, S. Gassen, 2017, Nature reviews. Immunology.

Unsupervised Trajectory Inference Using Graph Mining

Yvan Saeys, Sofie Van Gassen, Tom Dhaene, 2015, CIBB.

GroupEnc: encoder with group loss for global structure preservation

Y. Saeys, S. Gassen, David Novak, 2023, ArXiv.

Monocyte-driven atypical cytokine storm and aberrant neutrophil activation as key mediators of COVID-19 disease severity

J. Raes, Y. Saeys, D. Lambrechts, 2020, Nature Communications.

A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes

G. Nolan, G. McLachlan, Y. Saeys, 2016, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

Computational flow cytometry: helping to make sense of high-dimensional immunology data

Y. Saeys, B. Lambrecht, S. Gassen, 2016, Nature Reviews Immunology.