BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

192 related articles for article (PubMed ID: 18450006)

  • 21. MultiRTA: a simple yet reliable method for predicting peptide binding affinities for multiple class II MHC allotypes.
    Bordner AJ; Mittelmann HD
    BMC Bioinformatics; 2010 Sep; 11():482. PubMed ID: 20868497
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Predicting peptides that bind to MHC molecules using supervised learning of hidden Markov models.
    Mamitsuka H
    Proteins; 1998 Dec; 33(4):460-74. PubMed ID: 9849933
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Nonlinear predictive modeling of MHC class II-peptide binding using Bayesian neural networks.
    Winkler DA; Burden FR
    Methods Mol Biol; 2007; 409():365-77. PubMed ID: 18450015
    [TBL] [Abstract][Full Text] [Related]  

  • 24. A modular concept of HLA for comprehensive peptide binding prediction.
    DeLuca DS; Khattab B; Blasczyk R
    Immunogenetics; 2007 Jan; 59(1):25-35. PubMed ID: 17119951
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Proteins accessible to immune surveillance show significant T-cell epitope depletion: Implications for vaccine design.
    Halling-Brown M; Shaban R; Frampton D; Sansom CE; Davies M; Flower D; Duffield M; Titball RW; Brusic V; Moss DS
    Mol Immunol; 2009 Aug; 46(13):2699-705. PubMed ID: 19560824
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Methods and protocols for prediction of immunogenic epitopes.
    Tong JC; Tan TW; Ranganathan S
    Brief Bioinform; 2007 Mar; 8(2):96-108. PubMed ID: 17077136
    [TBL] [Abstract][Full Text] [Related]  

  • 27. POPI: predicting immunogenicity of MHC class I binding peptides by mining informative physicochemical properties.
    Tung CW; Ho SY
    Bioinformatics; 2007 Apr; 23(8):942-9. PubMed ID: 17384427
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Computational methods for prediction of T-cell epitopes--a framework for modelling, testing, and applications.
    Brusic V; Bajic VB; Petrovsky N
    Methods; 2004 Dec; 34(4):436-43. PubMed ID: 15542369
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Quantitative online prediction of peptide binding to the major histocompatibility complex.
    Hattotuwagama CK; Guan P; Doytchinova IA; Zygouri C; Flower DR
    J Mol Graph Model; 2004 Jan; 22(3):195-207. PubMed ID: 14629978
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Shift-invariant adaptive double threading: learning MHC II-peptide binding.
    Zaitlen N; Reyes-Gomez M; Heckerman D; Jojic N
    J Comput Biol; 2008 Sep; 15(7):927-42. PubMed ID: 18771399
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Deep convolutional neural networks for pan-specific peptide-MHC class I binding prediction.
    Han Y; Kim D
    BMC Bioinformatics; 2017 Dec; 18(1):585. PubMed ID: 29281985
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Prediction of MHC-binding peptides of flexible lengths from sequence-derived structural and physicochemical properties.
    Cui J; Han LY; Lin HH; Zhang HL; Tang ZQ; Zheng CJ; Cao ZW; Chen YZ
    Mol Immunol; 2007 Feb; 44(5):866-77. PubMed ID: 16806474
    [TBL] [Abstract][Full Text] [Related]  

  • 33. An iterative approach to class II predictions.
    Mallios RR
    Methods Mol Biol; 2007; 409():341-53. PubMed ID: 18450013
    [TBL] [Abstract][Full Text] [Related]  

  • 34. RBM-MHC: A Semi-Supervised Machine-Learning Method for Sample-Specific Prediction of Antigen Presentation by HLA-I Alleles.
    Bravi B; Tubiana J; Cocco S; Monasson R; Mora T; Walczak AM
    Cell Syst; 2021 Feb; 12(2):195-202.e9. PubMed ID: 33338400
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Peptide binding motif predictive algorithms correspond with experimental binding of leukemia vaccine candidate peptides to HLA-A*0201 molecules.
    Gomez-Nunez M; Pinilla-Ibarz J; Dao T; May RJ; Pao M; Jaggi JS; Scheinberg DA
    Leuk Res; 2006 Oct; 30(10):1293-8. PubMed ID: 16533527
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Structure-based prediction of protein-peptide specificity in Rosetta.
    King CA; Bradley P
    Proteins; 2010 Dec; 78(16):3437-49. PubMed ID: 20954182
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Structure-based prediction of MHC-peptide association: algorithm comparison and application to cancer vaccine design.
    Schiewe AJ; Haworth IS
    J Mol Graph Model; 2007 Oct; 26(3):667-75. PubMed ID: 17493854
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Predicting the MHC-peptide affinity using some interactive-type molecular descriptors and QSAR models.
    Lin TH
    Methods Mol Biol; 2007; 409():247-60. PubMed ID: 18450005
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Grouping of class I HLA alleles using electrostatic distribution maps of the peptide binding grooves.
    Kangueane P; Sakharkar MK
    Methods Mol Biol; 2007; 409():175-81. PubMed ID: 18450000
    [TBL] [Abstract][Full Text] [Related]  

  • 40. PromPDD, a web-based tool for the prediction, deciphering and design of promiscuous peptides that bind to HLA class I molecules.
    Zhang S; Chen J; Hong P; Li J; Tian Y; Wu Y; Wang S
    J Immunol Methods; 2020 Jan; 476():112685. PubMed ID: 31678214
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 10.