These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
3. Inference of kinase-signaling networks in human myeloid cell line models by Phosphoproteomics using kinase activity enrichment analysis (KAEA). Hallal M; Braga-Lagache S; Jankovic J; Simillion C; Bruggmann R; Uldry AC; Allam R; Heller M; Bonadies N BMC Cancer; 2021 Jul; 21(1):789. PubMed ID: 34238254 [TBL] [Abstract][Full Text] [Related]
4. Role of phosphoproteomics in the development of personalized cancer therapies. Cutillas PR Proteomics Clin Appl; 2015 Apr; 9(3-4):383-95. PubMed ID: 25488289 [TBL] [Abstract][Full Text] [Related]
5. Robust inference of kinase activity using functional networks. Yılmaz S; Ayati M; Schlatzer D; Çiçek AE; Chance MR; Koyutürk M Nat Commun; 2021 Feb; 12(1):1177. PubMed ID: 33608514 [TBL] [Abstract][Full Text] [Related]
6. Phosphoproteomics-Based Profiling of Kinase Activities in Cancer Cells. Wirbel J; Cutillas P; Saez-Rodriguez J Methods Mol Biol; 2018; 1711():103-132. PubMed ID: 29344887 [TBL] [Abstract][Full Text] [Related]
7. Kinase activity ranking using phosphoproteomics data (KARP) quantifies the contribution of protein kinases to the regulation of cell viability. Wilkes EH; Casado P; Rajeeve V; Cutillas PR Mol Cell Proteomics; 2017 Sep; 16(9):1694-1704. PubMed ID: 28674151 [TBL] [Abstract][Full Text] [Related]
8. Phosphotyrosine-based-phosphoproteomics scaled-down to biopsy level for analysis of individual tumor biology and treatment selection. Labots M; van der Mijn JC; Beekhof R; Piersma SR; de Goeij-de Haas RR; Pham TV; Knol JC; Dekker H; van Grieken NCT; Verheul HMW; Jiménez CR J Proteomics; 2017 Jun; 162():99-107. PubMed ID: 28442448 [TBL] [Abstract][Full Text] [Related]
9. An Optimized Chromatographic Strategy for Multiplexing In Parallel Reaction Monitoring Mass Spectrometry: Insights from Quantitation of Activated Kinases. Urisman A; Levin RS; Gordan JD; Webber JT; Hernandez H; Ishihama Y; Shokat KM; Burlingame AL Mol Cell Proteomics; 2017 Feb; 16(2):265-277. PubMed ID: 27940637 [TBL] [Abstract][Full Text] [Related]
10. Kinase-selective enrichment enables quantitative phosphoproteomics of the kinome across the cell cycle. Daub H; Olsen JV; Bairlein M; Gnad F; Oppermann FS; Körner R; Greff Z; Kéri G; Stemmann O; Mann M Mol Cell; 2008 Aug; 31(3):438-48. PubMed ID: 18691976 [TBL] [Abstract][Full Text] [Related]
11. An Integrative Analysis of Tumor Proteomic and Phosphoproteomic Profiles to Examine the Relationships Between Kinase Activity and Phosphorylation. Arshad OA; Danna V; Petyuk VA; Piehowski PD; Liu T; Rodland KD; McDermott JE Mol Cell Proteomics; 2019 Aug; 18(8 suppl 1):S26-S36. PubMed ID: 31227600 [TBL] [Abstract][Full Text] [Related]
12. Phosphoproteomics Profiling of Nonsmall Cell Lung Cancer Cells Treated with a Novel Phosphatase Activator. Wiredja DD; Ayati M; Mazhar S; Sangodkar J; Maxwell S; Schlatzer D; Narla G; Koyutürk M; Chance MR Proteomics; 2017 Nov; 17(22):. PubMed ID: 28961369 [TBL] [Abstract][Full Text] [Related]
13. Quantitative phosphoproteomic profiling of human non-small cell lung cancer tumors. Schweppe DK; Rigas JR; Gerber SA J Proteomics; 2013 Oct; 91():286-96. PubMed ID: 23911959 [TBL] [Abstract][Full Text] [Related]
14. Deep Phospho- and Phosphotyrosine Proteomics Identified Active Kinases and Phosphorylation Networks in Colorectal Cancer Cell Lines Resistant to Cetuximab. Abe Y; Nagano M; Kuga T; Tada A; Isoyama J; Adachi J; Tomonaga T Sci Rep; 2017 Sep; 7(1):10463. PubMed ID: 28874695 [TBL] [Abstract][Full Text] [Related]
15. Positive-unlabeled ensemble learning for kinase substrate prediction from dynamic phosphoproteomics data. Yang P; Humphrey SJ; James DE; Yang YH; Jothi R Bioinformatics; 2016 Jan; 32(2):252-9. PubMed ID: 26395771 [TBL] [Abstract][Full Text] [Related]
16. Large-scale proteomics analysis of the human kinome. Oppermann FS; Gnad F; Olsen JV; Hornberger R; Greff Z; Kéri G; Mann M; Daub H Mol Cell Proteomics; 2009 Jul; 8(7):1751-64. PubMed ID: 19369195 [TBL] [Abstract][Full Text] [Related]
17. In vivo phosphoproteomics reveals kinase activity profiles that predict treatment outcome in triple-negative breast cancer. Zagorac I; Fernandez-Gaitero S; Penning R; Post H; Bueno MJ; Mouron S; Manso L; Morente MM; Alonso S; Serra V; Muñoz J; Gómez-López G; Lopez-Acosta JF; Jimenez-Renard V; Gris-Oliver A; Al-Shahrour F; Piñeiro-Yañez E; Montoya-Suarez JL; Apala JV; Moreno-Torres A; Colomer R; Dopazo A; Heck AJR; Altelaar M; Quintela-Fandino M Nat Commun; 2018 Aug; 9(1):3501. PubMed ID: 30158526 [TBL] [Abstract][Full Text] [Related]
18. A Data-Driven Signaling Network Inference Approach for Phosphoproteomics. Madison I; Amin F; Song K; Sozzani R; Van den Broeck L Methods Mol Biol; 2023; 2690():335-354. PubMed ID: 37450158 [TBL] [Abstract][Full Text] [Related]
19. Quantitative analysis of cell signaling and drug action via mass spectrometry-based systems level phosphoproteomics. Tedford NC; Hall AB; Graham JR; Murphy CE; Gordon NF; Radding JA Proteomics; 2009 Mar; 9(6):1469-87. PubMed ID: 19294625 [TBL] [Abstract][Full Text] [Related]
20. PhosR enables processing and functional analysis of phosphoproteomic data. Kim HJ; Kim T; Hoffman NJ; Xiao D; James DE; Humphrey SJ; Yang P Cell Rep; 2021 Feb; 34(8):108771. PubMed ID: 33626354 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]