178 related articles for article (PubMed ID: 25044641)
1. Performance of super-SILAC based quantitative proteomics for comparison of different acute myeloid leukemia (AML) cell lines.
Aasebø E; Vaudel M; Mjaavatten O; Gausdal G; Van der Burgh A; Gjertsen BT; Døskeland SO; Bruserud O; Berven FS; Selheim F
Proteomics; 2014 Sep; 14(17-18):1971-6. PubMed ID: 25044641
[TBL] [Abstract][Full Text] [Related]
2. Freezing effects on the acute myeloid leukemia cell proteome and phosphoproteome revealed using optimal quantitative workflows.
Aasebø E; Mjaavatten O; Vaudel M; Farag Y; Selheim F; Berven F; Bruserud Ø; Hernandez-Valladares M
J Proteomics; 2016 Aug; 145():214-225. PubMed ID: 27107777
[TBL] [Abstract][Full Text] [Related]
3. The Implementation of Mass Spectrometry-Based Proteomics Workflows in Clinical Routines of Acute Myeloid Leukemia: Applicability and Perspectives.
Hernandez-Valladares M; Bruserud Ø; Selheim F
Int J Mol Sci; 2020 Sep; 21(18):. PubMed ID: 32957646
[TBL] [Abstract][Full Text] [Related]
4. Systematic evaluation of label-free and super-SILAC quantification for proteome expression analysis.
Tebbe A; Klammer M; Sighart S; Schaab C; Daub H
Rapid Commun Mass Spectrom; 2015 May; 29(9):795-801. PubMed ID: 26377007
[TBL] [Abstract][Full Text] [Related]
5. Proteomic profiles of human lung adeno and squamous cell carcinoma using super-SILAC and label-free quantification approaches.
Zhang W; Wei Y; Ignatchenko V; Li L; Sakashita S; Pham NA; Taylor P; Tsao MS; Kislinger T; Moran MF
Proteomics; 2014 Mar; 14(6):795-803. PubMed ID: 24453208
[TBL] [Abstract][Full Text] [Related]
6. Preservation Method and Phosphate Buffered Saline Washing Affect the Acute Myeloid Leukemia Proteome.
Wangen R; Aasebø E; Trentani A; Døskeland SO; Bruserud Ø; Selheim F; Hernandez-Valladares M
Int J Mol Sci; 2018 Jan; 19(1):. PubMed ID: 29351208
[TBL] [Abstract][Full Text] [Related]
7. EBprot: Statistical analysis of labeling-based quantitative proteomics data.
Koh HW; Swa HL; Fermin D; Ler SG; Gunaratne J; Choi H
Proteomics; 2015 Aug; 15(15):2580-91. PubMed ID: 25913743
[TBL] [Abstract][Full Text] [Related]
8. SILAC-based quantitative proteomic analysis of secretome between activated and reverted hepatic stellate cells.
Zhang H; Wu P; Chen F; Hao Y; Lao Y; Ren L; Sun L; Sun W; Wei H; Chan DW; Jiang Y; He F
Proteomics; 2014 Sep; 14(17-18):1977-86. PubMed ID: 24995952
[TBL] [Abstract][Full Text] [Related]
9. A comprehensive surface proteome analysis of myeloid leukemia cell lines for therapeutic antibody development.
Strassberger V; Gutbrodt KL; Krall N; Roesli C; Takizawa H; Manz MG; Fugmann T; Neri D
J Proteomics; 2014 Mar; 99():138-51. PubMed ID: 24487095
[TBL] [Abstract][Full Text] [Related]
10. A quantitative analysis of heterogeneities and hallmarks in acute myelogenous leukaemia.
Hu CW; Qiu Y; Ligeralde A; Raybon AY; Yoo SY; Coombes KR; Qutub AA; Kornblau SM
Nat Biomed Eng; 2019 Nov; 3(11):889-901. PubMed ID: 30988472
[TBL] [Abstract][Full Text] [Related]
11. Design and application of super-SILAC for proteome quantification.
Pozniak Y; Geiger T
Methods Mol Biol; 2014; 1188():281-91. PubMed ID: 25059619
[TBL] [Abstract][Full Text] [Related]
12. Proteomics of acute myeloid leukaemia: Cytogenetic risk groups differ specifically in their proteome, interactome and post-translational protein modifications.
Balkhi MY; Trivedi AK; Geletu M; Christopeit M; Bohlander SK; Behre HM; Behre G
Oncogene; 2006 Nov; 25(53):7041-58. PubMed ID: 16732326
[TBL] [Abstract][Full Text] [Related]
13. Proteomics-based strategy to identify biomarkers and pharmacological targets in leukemias with t(4;11) translocations.
Yocum AK; Busch CM; Felix CA; Blair IA
J Proteome Res; 2006 Oct; 5(10):2743-53. PubMed ID: 17022645
[TBL] [Abstract][Full Text] [Related]
14. Quantitative proteomics using SILAC: Principles, applications, and developments.
Chen X; Wei S; Ji Y; Guo X; Yang F
Proteomics; 2015 Sep; 15(18):3175-92. PubMed ID: 26097186
[TBL] [Abstract][Full Text] [Related]
15. Global Cell Proteome Profiling, Phospho-signaling and Quantitative Proteomics for Identification of New Biomarkers in Acute Myeloid Leukemia Patients.
Aasebø E; Forthun RB; Berven F; Selheim F; Hernandez-Valladares M
Curr Pharm Biotechnol; 2016; 17(1):52-70. PubMed ID: 26306748
[TBL] [Abstract][Full Text] [Related]
16. Dual phosphoproteomics and chemical proteomics analysis of erlotinib and gefitinib interference in acute myeloid leukemia cells.
Weber C; Schreiber TB; Daub H
J Proteomics; 2012 Feb; 75(4):1343-56. PubMed ID: 22115753
[TBL] [Abstract][Full Text] [Related]
17. Testing Suitability of Cell Cultures for SILAC-Experiments Using SWATH-Mass Spectrometry.
Reinders Y; Völler D; Bosserhoff AK; Oefner PJ; Reinders J
Methods Mol Biol; 2016; 1394():101-108. PubMed ID: 26700044
[TBL] [Abstract][Full Text] [Related]
18. Proteomics of microparticles with SILAC Quantification (PROMIS-Quan): a novel proteomic method for plasma biomarker quantification.
Harel M; Oren-Giladi P; Kaidar-Person O; Shaked Y; Geiger T
Mol Cell Proteomics; 2015 Apr; 14(4):1127-36. PubMed ID: 25624350
[TBL] [Abstract][Full Text] [Related]
19. Glucosyltransferase-dependent and -independent effects of TcdB on the proteome of HEp-2 cells.
Erdmann J; Junemann J; Schröder A; Just I; Gerhard R; Pich A
Proteomics; 2017 Aug; 17(15-16):. PubMed ID: 28612519
[TBL] [Abstract][Full Text] [Related]
20. Super-SILAC: current trends and future perspectives.
Shenoy A; Geiger T
Expert Rev Proteomics; 2015 Feb; 12(1):13-9. PubMed ID: 25404501
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
