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 *

192 related articles for article (PubMed ID: 32309431)

  • 41. Deep Conditional Random Field Approach to Transmembrane Topology Prediction and Application to GPCR Three-Dimensional Structure Modeling.
    Wu H; Wang K; Lu L; Xue Y; Lyu Q; Jiang M
    IEEE/ACM Trans Comput Biol Bioinform; 2017; 14(5):1106-1114. PubMed ID: 27576262
    [TBL] [Abstract][Full Text] [Related]  

  • 42. Improving AlphaFold predicted contacts in alpha-helical transmembrane proteins structures using structural features.
    Sawhney A; Li J; Liao L
    Res Sq; 2023 Oct; ():. PubMed ID: 37961476
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Prediction Enhancement of Residue Real-Value Relative Accessible Surface Area in Transmembrane Helical Proteins by Solving the Output Preference Problem of Machine Learning-Based Predictors.
    Xiao F; Shen HB
    J Chem Inf Model; 2015 Nov; 55(11):2464-74. PubMed ID: 26455366
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Analysis of deep learning methods for blind protein contact prediction in CASP12.
    Wang S; Sun S; Xu J
    Proteins; 2018 Mar; 86 Suppl 1(Suppl 1):67-77. PubMed ID: 28845538
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Why can deep convolutional neural networks improve protein fold recognition? A visual explanation by interpretation.
    Liu Y; Zhu YH; Song X; Song J; Yu DJ
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33537753
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Ensembling multiple raw coevolutionary features with deep residual neural networks for contact-map prediction in CASP13.
    Li Y; Zhang C; Bell EW; Yu DJ; Zhang Y
    Proteins; 2019 Dec; 87(12):1082-1091. PubMed ID: 31407406
    [TBL] [Abstract][Full Text] [Related]  

  • 47. An interpretable machine learning method for homo-trimeric protein interface residue-residue interaction prediction.
    Hong Z; Liu J; Chen Y
    Biophys Chem; 2021 Nov; 278():106666. PubMed ID: 34418678
    [TBL] [Abstract][Full Text] [Related]  

  • 48. Ab initio and template-based prediction of multi-class distance maps by two-dimensional recursive neural networks.
    Walsh I; Baù D; Martin AJ; Mooney C; Vullo A; Pollastri G
    BMC Struct Biol; 2009 Jan; 9():5. PubMed ID: 19183478
    [TBL] [Abstract][Full Text] [Related]  

  • 49. Topology of membrane proteins-predictions, limitations and variations.
    Tsirigos KD; Govindarajan S; Bassot C; Västermark Å; Lamb J; Shu N; Elofsson A
    Curr Opin Struct Biol; 2018 Jun; 50():9-17. PubMed ID: 29100082
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Deep architectures for protein contact map prediction.
    Di Lena P; Nagata K; Baldi P
    Bioinformatics; 2012 Oct; 28(19):2449-57. PubMed ID: 22847931
    [TBL] [Abstract][Full Text] [Related]  

  • 51. Recent Applications of Deep Learning Methods on Evolution- and Contact-Based Protein Structure Prediction.
    Suh D; Lee JW; Choi S; Lee Y
    Int J Mol Sci; 2021 Jun; 22(11):. PubMed ID: 34199677
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Improving transmembrane protein consensus topology prediction using inter-helical interaction.
    Wang H; Zhang C; Shi X; Zhang L; Zhou Y
    Biochim Biophys Acta; 2012 Nov; 1818(11):2679-86. PubMed ID: 22683598
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Folding Membrane Proteins by Deep Transfer Learning.
    Wang S; Li Z; Yu Y; Xu J
    Cell Syst; 2017 Sep; 5(3):202-211.e3. PubMed ID: 28957654
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Prediction of Metal Ion Binding Sites of Transmembrane Proteins.
    Qu J; Yin SS; Wang H
    Comput Math Methods Med; 2021; 2021():2327832. PubMed ID: 34721655
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Residue-Frustration-Based Prediction of Protein-Protein Interactions Using Machine Learning.
    Zhou X; Song H; Li J
    J Phys Chem B; 2022 Mar; 126(8):1719-1727. PubMed ID: 35170967
    [TBL] [Abstract][Full Text] [Related]  

  • 56. A two-stage approach for improved prediction of residue contact maps.
    Vullo A; Walsh I; Pollastri G
    BMC Bioinformatics; 2006 Mar; 7():180. PubMed ID: 16573808
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Modeling aspects of the language of life through transfer-learning protein sequences.
    Heinzinger M; Elnaggar A; Wang Y; Dallago C; Nechaev D; Matthes F; Rost B
    BMC Bioinformatics; 2019 Dec; 20(1):723. PubMed ID: 31847804
    [TBL] [Abstract][Full Text] [Related]  

  • 58. Machine learning in protein structure prediction.
    AlQuraishi M
    Curr Opin Chem Biol; 2021 Dec; 65():1-8. PubMed ID: 34015749
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Prediction of residue-residue contact matrix for protein-protein interaction with Fisher score features and deep learning.
    Du T; Liao L; Wu CH; Sun B
    Methods; 2016 Nov; 110():97-105. PubMed ID: 27282356
    [TBL] [Abstract][Full Text] [Related]  

  • 60. Lipid exposure prediction enhances the inference of rotational angles of transmembrane helices.
    Lai JS; Cheng CW; Lo A; Sung TY; Hsu WL
    BMC Bioinformatics; 2013 Oct; 14():304. PubMed ID: 24112406
    [TBL] [Abstract][Full Text] [Related]  

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