208 related articles for article (PubMed ID: 31577391)
1. An R-Derived FlowSOM Process to Analyze Unsupervised Clustering of Normal and Malignant Human Bone Marrow Classical Flow Cytometry Data.
Lacombe F; Lechevalier N; Vial JP; Béné MC
Cytometry A; 2019 Nov; 95(11):1191-1197. PubMed ID: 31577391
[TBL] [Abstract][Full Text] [Related]
2. Unsupervised Flow Cytometry Analysis Allows for an Accurate Identification of Minimal Residual Disease Assessment in Acute Myeloid Leukemia.
Vial JP; Lechevalier N; Lacombe F; Dumas PY; Bidet A; Leguay T; Vergez F; Pigneux A; Béné MC
Cancers (Basel); 2021 Feb; 13(4):. PubMed ID: 33562525
[TBL] [Abstract][Full Text] [Related]
3. Unsupervised flow cytometry analysis in hematological malignancies: A new paradigm.
Béné MC; Lacombe F; Porwit A
Int J Lab Hematol; 2021 Jul; 43 Suppl 1():54-64. PubMed ID: 34288436
[TBL] [Abstract][Full Text] [Related]
4. Monitoring of minimal residual disease in acute leukemia by multiparametric flow cytometry.
Kusenda J; Fajtova M; Kovarikova A
Neoplasma; 2014; 61(2):119-27. PubMed ID: 24299307
[TBL] [Abstract][Full Text] [Related]
5. Methodological aspects of minimal residual disease assessment by flow cytometry in acute lymphoblastic leukemia: A French multicenter study.
Fossat C; Roussel M; Arnoux I; Asnafi V; Brouzes C; Garnache-Ottou F; Jacob MC; Kuhlein E; Macintyre-Davi E; Plesa A; Robillard N; Tkaczuk J; Ifrah N; Dombret H; Béné MC; Baruchel A; Garand R;
Cytometry B Clin Cytom; 2015 Jan; 88(1):21-9. PubMed ID: 25363877
[TBL] [Abstract][Full Text] [Related]
6. Automated Flow Cytometric MRD Assessment in Childhood Acute B- Lymphoblastic Leukemia Using Supervised Machine Learning.
Reiter M; Diem M; Schumich A; Maurer-Granofszky M; Karawajew L; Rossi JG; Ratei R; Groeneveld-Krentz S; Sajaroff EO; Suhendra S; Kampel M; Dworzak MN;
Cytometry A; 2019 Sep; 95(9):966-975. PubMed ID: 31282025
[TBL] [Abstract][Full Text] [Related]
7. Phenotypic Analysis of Hematopoietic Stem and Progenitor Cell Populations in Acute Myeloid Leukemia Based on Spectral Flow Cytometry, a 20-Color Panel, and Unsupervised Learning Algorithms.
Matthes T
Int J Mol Sci; 2024 Feb; 25(5):. PubMed ID: 38474094
[TBL] [Abstract][Full Text] [Related]
8. The applicability of multiparameter flow cytometry for the detection of minimal residual disease using different-from-normal panels to predict relapse in patients with acute myeloid leukemia after allogeneic transplantation.
Wang Z; Guo M; Zhang Y; Xu S; Cheng H; Wu J; Zhang W; Hu X; Yang J; Wang J; Tang G
Int J Lab Hematol; 2019 Oct; 41(5):607-614. PubMed ID: 31162830
[TBL] [Abstract][Full Text] [Related]
9. Flow cytometry of peripheral blood and bone marrow cells from patients with hairy cell leukemia: phenotype of hairy cells, lymphocyte subsets and detection of minimal residual disease after treatment.
Babuŝíková O; Tomová A; Kusenda J; Gyárfás J
Neoplasma; 2001; 48(5):350-7. PubMed ID: 11845978
[TBL] [Abstract][Full Text] [Related]
10. Discriminant function analysis as decision support system for the diagnosis of acute leukemia with a minimal four color screening panel and multiparameter flow cytometry immunophenotyping.
Ratei R; Karawajew L; Lacombe F; Jagoda K; Del Poeta G; Kraan J; De Santiago M; Kappelmayer J; Björklund E; Ludwig WD; Gratama JW; Orfao A;
Leukemia; 2007 Jun; 21(6):1204-11. PubMed ID: 17410192
[TBL] [Abstract][Full Text] [Related]
11. Evaluation of new markers for minimal residual disease monitoring in B-cell precursor acute lymphoblastic leukemia: CD73 and CD86 are the most relevant new markers to increase the efficacy of MRD 2016; 00B: 000-000.
Tembhare PR; Ghogale S; Ghatwai N; Badrinath Y; Kunder N; Patkar NV; Bibi AR; Chatterjee G; Arora B; Narula G; Banawali S; Deshpande N; Amare P; Gujral S; Subramanian PG
Cytometry B Clin Cytom; 2018 Jan; 94(1):100-111. PubMed ID: 27718302
[TBL] [Abstract][Full Text] [Related]
12. Immunophenotypic analysis of CD19+ precursors in normal human adult bone marrow: implications for minimal residual disease detection.
Ciudad J; Orfao A; Vidriales B; Macedo A; Martínez A; González M; López-Berges MC; Valverde B; San Miguel JF
Haematologica; 1998 Dec; 83(12):1069-75. PubMed ID: 9949623
[TBL] [Abstract][Full Text] [Related]
13. The clinical significance of negative flow cytometry immunophenotypic results in a morphologically scored positive bone marrow in patients following treatment for acute myeloid leukemia.
Ouyang J; Goswami M; Tang G; Peng J; Ravandi F; Daver N; Routbort M; Konoplev S; Lin P; Medeiros LJ; Jorgensen JL; Wang SA
Am J Hematol; 2015 Jun; 90(6):504-10. PubMed ID: 25732229
[TBL] [Abstract][Full Text] [Related]
14. Unsupervised cluster analysis and subset characterization of abnormal erythropoiesis using the bioinformatic Flow-Self Organizing Maps algorithm.
Porwit A; Violidaki D; Axler O; Lacombe F; Ehinger M; Béné MC
Cytometry B Clin Cytom; 2022 Mar; 102(2):134-142. PubMed ID: 35150187
[TBL] [Abstract][Full Text] [Related]
15. Computational flow cytometry provides accurate assessment of measurable residual disease in chronic lymphocytic leukaemia.
Nguyen PC; Nguyen V; Baldwin K; Kankanige Y; Blombery P; Came N; Westerman DA
Br J Haematol; 2023 Aug; 202(4):760-770. PubMed ID: 37052611
[TBL] [Abstract][Full Text] [Related]
16. Automated and simplified identification of normal and abnormal plasma cells in Multiple Myeloma by flow cytometry.
Alaterre E; Raimbault S; Garcia JM; Rème T; Requirand G; Klein B; Moreaux J
Cytometry B Clin Cytom; 2018 May; 94(3):484-492. PubMed ID: 28865180
[TBL] [Abstract][Full Text] [Related]
17. Comparison of Multiparameter Flow Cytometry Immunophenotypic Analysis and Quantitative RT-PCR for the Detection of Minimal Residual Disease of Core Binding Factor Acute Myeloid Leukemia.
Ouyang J; Goswami M; Peng J; Zuo Z; Daver N; Borthakur G; Tang G; Medeiros LJ; Jorgensen JL; Ravandi F; Wang SA
Am J Clin Pathol; 2016 Jun; 145(6):769-77. PubMed ID: 27298396
[TBL] [Abstract][Full Text] [Related]
18. Detection and monitoring of normal and leukemic cell populations with hierarchical clustering of flow cytometry data.
Fišer K; Sieger T; Schumich A; Wood B; Irving J; Mejstříková E; Dworzak MN
Cytometry A; 2012 Jan; 81(1):25-34. PubMed ID: 21990127
[TBL] [Abstract][Full Text] [Related]
19. Flow cytometric analysis of normal B cell differentiation: a frame of reference for the detection of minimal residual disease in precursor-B-ALL.
Lúcio P; Parreira A; van den Beemd MW; van Lochem EG; van Wering ER; Baars E; Porwit-MacDonald A; Bjorklund E; Gaipa G; Biondi A; Orfao A; Janossy G; van Dongen JJ; San Miguel JF
Leukemia; 1999 Mar; 13(3):419-27. PubMed ID: 10086733
[TBL] [Abstract][Full Text] [Related]
20. Comprehensive Protocol to Sample and Process Bone Marrow for Measuring Measurable Residual Disease and Leukemic Stem Cells in Acute Myeloid Leukemia.
Cloos J; Harris JR; Janssen JJWM; Kelder A; Huang F; Sijm G; Vonk M; Snel AN; Scheick JR; Scholten WJ; Carbaat-Ham J; Veldhuizen D; Hanekamp D; Oussoren-Brockhoff YJM; Kaspers GJL; Schuurhuis GJ; Sasser AK; Ossenkoppele G
J Vis Exp; 2018 Mar; (133):. PubMed ID: 29553571
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
