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1.
Splicing factor-mediated regulation patterns reveals biological characteristics and aid in predicting prognosis in acute myeloid leukemia.
J Transl Med
; 21(1): 6, 2023 01 07.
Artículo
en Inglés
| MEDLINE | ID: mdl-36611187
2.
Molecular subtypes predict therapeutic responses and identifying and validating diagnostic signatures based on machine learning in chronic myeloid leukemia.
Cancer Cell Int
; 23(1): 61, 2023 Apr 06.
Artículo
en Inglés
| MEDLINE | ID: mdl-37024911
3.
A novel fatty acid metabolism-related signature identifies features of the tumor microenvironment and predicts clinical outcome in acute myeloid leukemia.
Lipids Health Dis
; 21(1): 79, 2022 Aug 25.
Artículo
en Inglés
| MEDLINE | ID: mdl-36002858
4.
A Novel Necroptosis-Related Signature Can Predict Prognosis and Chemotherapy Sensitivity in Multiple Myeloma.
Technol Cancer Res Treat
; 23: 15330338241232554, 2024.
Artículo
en Inglés
| MEDLINE | ID: mdl-38361483
5.
Application of interpretable machine learning algorithms to predict distant metastasis in ovarian clear cell carcinoma.
Cancer Med
; 13(7): e7161, 2024 Apr.
Artículo
en Inglés
| MEDLINE | ID: mdl-38613173
6.
Inflammatory response mediates cross-talk with immune function and reveals clinical features in acute myeloid leukemia.
Biosci Rep
; 42(5)2022 05 27.
Artículo
en Inglés
| MEDLINE | ID: mdl-35441668
7.
Ferroptosis-related molecular patterns reveal immune escape, inflammatory development and lipid metabolism characteristics of the tumor microenvironment in acute myeloid leukemia.
Front Oncol
; 12: 888570, 2022.
Artículo
en Inglés
| MEDLINE | ID: mdl-36518303
8.
m(6)A Modification of lncRNA NEAT1 Regulates Chronic Myelocytic Leukemia Progression via miR-766-5p/CDKN1A Axis.
Front Oncol
; 11: 679634, 2021.
Artículo
en Inglés
| MEDLINE | ID: mdl-34354942
9.
Quantitative Proteomic Analysis of Plasma Exosomes to Identify the Candidate Biomarker of Imatinib Resistance in Chronic Myeloid Leukemia Patients.
Front Oncol
; 11: 779567, 2021.
Artículo
en Inglés
| MEDLINE | ID: mdl-34993140
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