The machine-learning classifier ALLCatchR2 identifies 20 T-ALL subtypes across cohorts and age groups.

Beder T, Wolgast N, Walter W, Bendig S, Hartmann AM, Barz MJ, Zaliova M, Reitzel ES, Baden D, Schwartz S, Gökbuget N, Kester L, Trka J, Haferlach C, Brüggemann M, Baldus CD, Neumann M, Bastian L

Open source

DOI: 10.1002/hem3.70475
Published: 2026 Sep
Container: HemaSphere
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1002/hem3.70475,
  title = {The machine-learning classifier ALLCatchR2 identifies 20 T-ALL subtypes across cohorts and age groups.},
  author = {Beder T and Wolgast N and Walter W and Bendig S and Hartmann AM and Barz MJ and Zaliova M and Reitzel ES and Baden D and Schwartz S and Gökbuget N and Kester L and Trka J and Haferlach C and Brüggemann M and Baldus CD and Neumann M and Bastian L},
  year = {2026},
  journal = {HemaSphere},
  doi = {10.1002/hem3.70475},
  url = {https://doi.org/10.1002/hem3.70475}
}

RIS

TY  - JOUR
TI  - The machine-learning classifier ALLCatchR2 identifies 20 T-ALL subtypes across cohorts and age groups.
AU  - Beder T
AU  - Wolgast N
AU  - Walter W
AU  - Bendig S
AU  - Hartmann AM
AU  - Barz MJ
AU  - Zaliova M
AU  - Reitzel ES
AU  - Baden D
AU  - Schwartz S
AU  - Gökbuget N
AU  - Kester L
AU  - Trka J
AU  - Haferlach C
AU  - Brüggemann M
AU  - Baldus CD
AU  - Neumann M
AU  - Bastian L
PY  - 2026
JO  - HemaSphere
DO  - 10.1002/hem3.70475
UR  - https://doi.org/10.1002/hem3.70475
ER  -

APA

T, B., N, W., W, W., S, B., AM, H., MJ, B., M, Z., ES, R., D, B., S, S., N, G., L, K., J, T., C, H., M, B., CD, B., M, N., & L, B. (2026). The machine-learning classifier ALLCatchR2 identifies 20 T-ALL subtypes across cohorts and age groups.. HemaSphere. https://doi.org/10.1002/hem3.70475

Source records

pubmed · retrieved 2026-09-26T23:51:03.539Z