Predicting single cell genotypes from single cell expression profiles in AML using deep learning-Reference-Cited by-同舟云学术

Predicting single cell genotypes from single cell expression profiles in AML using deep learning

Published:2023-01-13 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 12th International Conference on Bioscience, Biochemistry and Bioinformatics
language:
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Author:

Asimomitis Georgios¹^ORCID,Sirenko Maria²^ORCID,Fotis Christos³^ORCID,Landau Dan A⁴^ORCID,Alexopoulos Leonidas G⁵^ORCID,Papaemmanuil Elli²^ORCID

Affiliation:

1. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, USA and Biomedical Systems Laboratory, Department of Mechanical Engineering, National Technical University of Athens, Greece

2. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, USA

3. ProtATonce Ltd, Demokritos Science Park, Greece

4. Meyer Cancer Center, Weill Cornell Medicine, USA

5. Biomedical Systems Laboratory, Department of Mechanical Engineering, National Technical University of Athens, Greece

Funder

National Institutes of Health

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3586139.3586140

Reference30 articles.

1. Exploring single-cell data with deep multitasking neural networks;Amodio Matthew;Nat. Methods,2019

2. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia;Arber Daniel A.;Blood,2016

3. Targeting NF-κB in hematologic malignancies;Braun T.;Cell Death & Differentiation,2006

4. Therapeutic Advances in Acute Myeloid Leukemia;Burnett Alan;Journal of Clinical Oncology,2011

5. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel;Döhner Hartmut;Blood,2017