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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

169 related articles for article (PubMed ID: 36692152)

  • 21. Predicting protein phosphorylation sites in soybean using interpretable deep tabular learning network.
    Khalili E; Ramazi S; Ghanati F; Kouchaki S
    Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35152280
    [TBL] [Abstract][Full Text] [Related]  

  • 22. In Vitro Kinase-to-Phosphosite Database (iKiP-DB) Predicts Kinase Activity in Phosphoproteomic Datasets.
    Mari T; Mösbauer K; Wyler E; Landthaler M; Drosten C; Selbach M
    J Proteome Res; 2022 Jun; 21(6):1575-1587. PubMed ID: 35608653
    [TBL] [Abstract][Full Text] [Related]  

  • 23. A generic deep convolutional neural network framework for prediction of receptor-ligand interactions-NetPhosPan: application to kinase phosphorylation prediction.
    Fenoy E; Izarzugaza JMG; Jurtz V; Brunak S; Nielsen M
    Bioinformatics; 2019 Apr; 35(7):1098-1107. PubMed ID: 30169744
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Capsule network for protein post-translational modification site prediction.
    Wang D; Liang Y; Xu D
    Bioinformatics; 2019 Jul; 35(14):2386-2394. PubMed ID: 30520972
    [TBL] [Abstract][Full Text] [Related]  

  • 25. 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]  

  • 26. Co-phosphorylation networks reveal subtype-specific signaling modules in breast cancer.
    Ayati M; Chance MR; Koyutürk M
    Bioinformatics; 2021 Apr; 37(2):221-228. PubMed ID: 32730576
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Identifying protein phosphorylation sites with kinase substrate specificity on human viruses.
    Bretaña NA; Lu CT; Chiang CY; Su MG; Huang KY; Lee TY; Weng SL
    PLoS One; 2012; 7(7):e40694. PubMed ID: 22844408
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Prediction of protein kinase-specific phosphorylation sites in hierarchical structure using functional information and random forest.
    Fan W; Xu X; Shen Y; Feng H; Li A; Wang M
    Amino Acids; 2014 Apr; 46(4):1069-78. PubMed ID: 24452754
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Deciphering kinase-substrate relationships by analysis of domain-specific phosphorylation network.
    Damle NP; Mohanty D
    Bioinformatics; 2014 Jun; 30(12):1730-8. PubMed ID: 24574117
    [TBL] [Abstract][Full Text] [Related]  

  • 30. PhosContext2vec: a distributed representation of residue-level sequence contexts and its application to general and kinase-specific phosphorylation site prediction.
    Xu Y; Song J; Wilson C; Whisstock JC
    Sci Rep; 2018 May; 8(1):8240. PubMed ID: 29844483
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Prediction of kinase-specific phosphorylation sites through an integrative model of protein context and sequence.
    Patrick R; Horin C; Kobe B; Cao KA; Bodén M
    Biochim Biophys Acta; 2016 Nov; 1864(11):1599-608. PubMed ID: 27507704
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Machine learning empowers phosphoproteome prediction in cancers.
    Li H; Guan Y
    Bioinformatics; 2020 Feb; 36(3):859-864. PubMed ID: 31410451
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Quokka: a comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome.
    Li F; Li C; Marquez-Lago TT; Leier A; Akutsu T; Purcell AW; Ian Smith A; Lithgow T; Daly RJ; Song J; Chou KC
    Bioinformatics; 2018 Dec; 34(24):4223-4231. PubMed ID: 29947803
    [TBL] [Abstract][Full Text] [Related]  

  • 34. From sequence to structural analysis in protein phosphorylation motifs.
    Via A; Diella F; Gibson TJ; Helmer-Citterich M
    Front Biosci (Landmark Ed); 2011 Jan; 16(4):1261-75. PubMed ID: 21196230
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Large-scale Discovery of Substrates of the Human Kinome.
    Sugiyama N; Imamura H; Ishihama Y
    Sci Rep; 2019 Jul; 9(1):10503. PubMed ID: 31324866
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Cooperativity within proximal phosphorylation sites is revealed from large-scale proteomics data.
    Schweiger R; Linial M
    Biol Direct; 2010 Jan; 5():6. PubMed ID: 20100358
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Accurate prediction of kinase-substrate networks using knowledge graphs.
    Nováček V; McGauran G; Matallanas D; Vallejo Blanco A; Conca P; Muñoz E; Costabello L; Kanakaraj K; Nawaz Z; Walsh B; Mohamed SK; Vandenbussche PY; Ryan CJ; Kolch W; Fey D
    PLoS Comput Biol; 2020 Dec; 16(12):e1007578. PubMed ID: 33270624
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Protein kinases phosphorylate long disordered regions in intrinsically disordered proteins.
    Koike R; Amano M; Kaibuchi K; Ota M
    Protein Sci; 2020 Feb; 29(2):564-571. PubMed ID: 31724233
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Rapid Identification of Protein Kinase Phosphorylation Site Motifs Using Combinatorial Peptide Libraries.
    Miller CJ; Turk BE
    Methods Mol Biol; 2016; 1360():203-16. PubMed ID: 26501912
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Functional characterization of co-phosphorylation networks.
    Ayati M; Yılmaz S; Chance MR; Koyuturk M
    Bioinformatics; 2022 Aug; 38(15):3785-3793. PubMed ID: 35731218
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.