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 *

120 related articles for article (PubMed ID: 27074717)

  • 1. SPAR: a random forest-based predictor for self-interacting proteins with fine-grained domain information.
    Liu X; Yang S; Li C; Zhang Z; Song J
    Amino Acids; 2016 Jul; 48(7):1655-65. PubMed ID: 27074717
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Critical assessment and performance improvement of plant-pathogen protein-protein interaction prediction methods.
    Yang S; Li H; He H; Zhou Y; Zhang Z
    Brief Bioinform; 2019 Jan; 20(1):274-287. PubMed ID: 29028906
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine-Learning-Based Predictor of Human-Bacteria Protein-Protein Interactions by Incorporating Comprehensive Host-Network Properties.
    Lian X; Yang S; Li H; Fu C; Zhang Z
    J Proteome Res; 2019 May; 18(5):2195-2205. PubMed ID: 30983371
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Multiple classifier integration for the prediction of protein structural classes.
    Chen L; Lu L; Feng K; Li W; Song J; Zheng L; Yuan Y; Zeng Z; Feng K; Lu W; Cai Y
    J Comput Chem; 2009 Nov; 30(14):2248-54. PubMed ID: 19274708
    [TBL] [Abstract][Full Text] [Related]  

  • 5. PRBP: Prediction of RNA-Binding Proteins Using a Random Forest Algorithm Combined with an RNA-Binding Residue Predictor.
    Ma X; Guo J; Xiao K; Sun X
    IEEE/ACM Trans Comput Biol Bioinform; 2015; 12(6):1385-93. PubMed ID: 26671809
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A Feature and Algorithm Selection Method for Improving the Prediction of Protein Structural Class.
    Ni Q; Chen L
    Comb Chem High Throughput Screen; 2017; 20(7):612-621. PubMed ID: 28292249
    [TBL] [Abstract][Full Text] [Related]  

  • 7. SuccinSite: a computational tool for the prediction of protein succinylation sites by exploiting the amino acid patterns and properties.
    Hasan MM; Yang S; Zhou Y; Mollah MN
    Mol Biosyst; 2016 Mar; 12(3):786-95. PubMed ID: 26739209
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Accurate in silico identification of protein succinylation sites using an iterative semi-supervised learning technique.
    Zhao X; Ning Q; Chai H; Ma Z
    J Theor Biol; 2015 Jun; 374():60-5. PubMed ID: 25843215
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Prediction of interactions between viral and host proteins using supervised machine learning methods.
    Barman RK; Saha S; Das S
    PLoS One; 2014; 9(11):e112034. PubMed ID: 25375323
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Statistical geometry based prediction of nonsynonymous SNP functional effects using random forest and neuro-fuzzy classifiers.
    Barenboim M; Masso M; Vaisman II; Jamison DC
    Proteins; 2008 Jun; 71(4):1930-9. PubMed ID: 18186470
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Highly accurate prediction of protein self-interactions by incorporating the average block and PSSM information into the general PseAAC.
    Zhai JX; Cao TJ; An JY; Bian YT
    J Theor Biol; 2017 Nov; 432():80-86. PubMed ID: 28802824
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Learning protein multi-view features in complex space.
    Yu DJ; Hu J; Wu XW; Shen HB; Chen J; Tang ZM; Yang J; Yang JY
    Amino Acids; 2013 May; 44(5):1365-79. PubMed ID: 23456487
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Prediction of active sites of enzymes by maximum relevance minimum redundancy (mRMR) feature selection.
    Gao YF; Li BQ; Cai YD; Feng KY; Li ZD; Jiang Y
    Mol Biosyst; 2013 Jan; 9(1):61-9. PubMed ID: 23117653
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Prediction of human-virus protein-protein interactions through a sequence embedding-based machine learning method.
    Yang X; Yang S; Li Q; Wuchty S; Zhang Z
    Comput Struct Biotechnol J; 2020; 18():153-161. PubMed ID: 31969974
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Prediction of fatty acid-binding residues on protein surfaces with three-dimensional probability distributions of interacting atoms.
    Mahalingam R; Peng HP; Yang AS
    Biophys Chem; 2014 Aug; 192():10-9. PubMed ID: 24934883
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Meta-DP: domain prediction meta-server.
    Saini HK; Fischer D
    Bioinformatics; 2005 Jun; 21(12):2917-20. PubMed ID: 15840708
    [TBL] [Abstract][Full Text] [Related]  

  • 17. DNABP: Identification of DNA-Binding Proteins Based on Feature Selection Using a Random Forest and Predicting Binding Residues.
    Ma X; Guo J; Sun X
    PLoS One; 2016; 11(12):e0167345. PubMed ID: 27907159
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection.
    Ma X; Guo J; Sun X
    Biomed Res Int; 2015; 2015():425810. PubMed ID: 26543860
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Prediction of protein-protein interaction sites by random forest algorithm with mRMR and IFS.
    Li BQ; Feng KY; Chen L; Huang T; Cai YD
    PLoS One; 2012; 7(8):e43927. PubMed ID: 22937126
    [TBL] [Abstract][Full Text] [Related]  

  • 20. hCKSAAP_UbSite: improved prediction of human ubiquitination sites by exploiting amino acid pattern and properties.
    Chen Z; Zhou Y; Song J; Zhang Z
    Biochim Biophys Acta; 2013 Aug; 1834(8):1461-7. PubMed ID: 23603789
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.