A mixed-effects stochastic model reveals clonal dominance in gene therapy safety studies

Background Mathematical models of haematopoiesis can provide insights on abnormal cell expansions (clonal dominance), and in turn can guide safety monitoring in gene therapy clinical applications. Clonal tracking is a recent high-throughput technology that can be used to quantify cells arising from...

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Bibliographic Details
Published in:	BMC bioinformatics Vol. 24; no. 1; pp. 228 - 19
Main Authors:	Del Core, Luca, Pellin, Danilo, Wit, Ernst C., Grzegorczyk, Marco A.
Format:	Journal Article
Language:	English
Published:	London BioMed Central 02.06.2023 BioMed Central Ltd Springer Nature B.V BMC
Subjects:	Algorithms Analysis Approximation Bioinformatics Biomedical and Life Sciences Cell death Cell differentiation Clonal dominance Clone Cells Cloning Computational Biology/Bioinformatics Computer Appl. in Life Sciences Computer Simulation Differential equations Dominance E-M algorithm Gene therapy Generalized linear models Genes Genetic aspects Hematopoietic stem cells Hemopoiesis Heterogeneity Learning models (Stochastic processes) Life Sciences Likelihood Functions Mathematical models Microarrays Mixed-effects models Models, Theoretical Mutagenesis Parameters Population biology Population dynamics Safety Safety analysis Safety and security measures Single-cell technologies Statistical models Stem cell research Stem cells Stochastic models Stochastic Processes Stochastic reaction networks tau$$ τ -Leaping Tracking Transplantation Netherlands Stochastic reaction networks Leaping Gene therapy Clonal dominance Mixed-effects models E-M algorithm
ISSN:	1471-2105, 1471-2105
Online Access:	Get full text
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