Predicting time to relapse in acute myeloid leukemia through stochastic modeling of minimal residual disease based on clonality data

Dinh, K. N., Jaksik, R., Corey, S. J., & Kimmel, M. (2021). Predicting time to relapse in acute myeloid leukemia through stochastic modeling of minimal residual disease based on clonality data. Computational and Systems Oncology, 1(3). Portico. https://doi.org/10.1002/cso2.1026
Authors:
Khanh N. Dinh
Roman Jaksik
Seth J. Corey
Marek Kimmel
Affiliated Authors:
Khanh N. Dinh
Columbia Affiliation:
Subjects:
Acute Myeloid Leukemia (OpenAlex Topic)
Genomic Landscape of Cancer and Mutational Signatures (OpenAlex Topic)
Molecular Pathogenesis of Myeloproliferative Disorders (OpenAlex Topic)
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Publication Type:
Article
Unique ID:
10.1002/cso2.1026
PMID:
34541576
DOI:
10.1002/cso2.1026
Journal:
Computational and Systems Oncology
Publication Date:
Data Source:
OpenAlex
Source Link:
View OpenAlex Record

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