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 *

155 related articles for article (PubMed ID: 20376314)

  • 41. Ens-PPI: A Novel Ensemble Classifier for Predicting the Interactions of Proteins Using Autocovariance Transformation from PSSM.
    Gao ZG; Wang L; Xia SX; You ZH; Yan X; Zhou Y
    Biomed Res Int; 2016; 2016():4563524. PubMed ID: 27437399
    [TBL] [Abstract][Full Text] [Related]  

  • 42. An SVM-based system for predicting protein subnuclear localizations.
    Lei Z; Dai Y
    BMC Bioinformatics; 2005 Dec; 6():291. PubMed ID: 16336650
    [TBL] [Abstract][Full Text] [Related]  

  • 43. MiRTif: a support vector machine-based microRNA target interaction filter.
    Yang Y; Wang YP; Li KB
    BMC Bioinformatics; 2008 Dec; 9 Suppl 12(Suppl 12):S4. PubMed ID: 19091027
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Network-based prediction and knowledge mining of disease genes.
    Carson MB; Lu H
    BMC Med Genomics; 2015; 8 Suppl 2(Suppl 2):S9. PubMed ID: 26043920
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Prediction of miRNA targets.
    Oulas A; Karathanasis N; Louloupi A; Pavlopoulos GA; Poirazi P; Kalantidis K; Iliopoulos I
    Methods Mol Biol; 2015; 1269():207-29. PubMed ID: 25577381
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Kernel based machine learning algorithm for the efficient prediction of type III polyketide synthase family of proteins.
    Mallika V; Sivakumar KC; Jaichand S; Soniya EV
    J Integr Bioinform; 2010 Jul; 7(1):. PubMed ID: 20625199
    [TBL] [Abstract][Full Text] [Related]  

  • 47. PCHM: A bioinformatic resource for high-throughput human mitochondrial proteome searching and comparison.
    Kim T; Kim E; Park SJ; Joo H
    Comput Biol Med; 2009 Aug; 39(8):689-96. PubMed ID: 19541297
    [TBL] [Abstract][Full Text] [Related]  

  • 48. LEARNING PARSIMONIOUS ENSEMBLES FOR UNBALANCED COMPUTATIONAL GENOMICS PROBLEMS.
    Stanescu A; Pandey G
    Pac Symp Biocomput; 2017; 22():288-299. PubMed ID: 27896983
    [TBL] [Abstract][Full Text] [Related]  

  • 49. NL MIND-BEST: a web server for ligands and proteins discovery--theoretic-experimental study of proteins of Giardia lamblia and new compounds active against Plasmodium falciparum.
    González-Díaz H; Prado-Prado F; Sobarzo-Sánchez E; Haddad M; Maurel Chevalley S; Valentin A; Quetin-Leclercq J; Dea-Ayuela MA; Teresa Gomez-Muños M; Munteanu CR; José Torres-Labandeira J; García-Mera X; Tapia RA; Ubeira FM
    J Theor Biol; 2011 May; 276(1):229-49. PubMed ID: 21277861
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure.
    Lewis DP; Jebara T; Noble WS
    Bioinformatics; 2006 Nov; 22(22):2753-60. PubMed ID: 16966363
    [TBL] [Abstract][Full Text] [Related]  

  • 51. LIBRUS: combined machine learning and homology information for sequence-based ligand-binding residue prediction.
    Kauffman C; Karypis G
    Bioinformatics; 2009 Dec; 25(23):3099-107. PubMed ID: 19786483
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Filtering high-throughput protein-protein interaction data using a combination of genomic features.
    Patil A; Nakamura H
    BMC Bioinformatics; 2005 Apr; 6():100. PubMed ID: 15833142
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Improving protein-protein interactions prediction accuracy using protein evolutionary information and relevance vector machine model.
    An JY; Meng FR; You ZH; Chen X; Yan GY; Hu JP
    Protein Sci; 2016 Oct; 25(10):1825-33. PubMed ID: 27452983
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Prediction of protein-RNA binding sites by a random forest method with combined features.
    Liu ZP; Wu LY; Wang Y; Zhang XS; Chen L
    Bioinformatics; 2010 Jul; 26(13):1616-22. PubMed ID: 20483814
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods.
    Lise S; Archambeau C; Pontil M; Jones DT
    BMC Bioinformatics; 2009 Oct; 10():365. PubMed ID: 19878545
    [TBL] [Abstract][Full Text] [Related]  

  • 56. Protein Residue Contacts and Prediction Methods.
    Adhikari B; Cheng J
    Methods Mol Biol; 2016; 1415():463-76. PubMed ID: 27115648
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics.
    Li ZW; You ZH; Chen X; Gui J; Nie R
    Int J Mol Sci; 2016 Aug; 17(9):. PubMed ID: 27571061
    [TBL] [Abstract][Full Text] [Related]  

  • 58. Accurate prediction of stability changes in protein mutants by combining machine learning with structure based computational mutagenesis.
    Masso M; Vaisman II
    Bioinformatics; 2008 Sep; 24(18):2002-9. PubMed ID: 18632749
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Identification of cavities on protein surface using multiple computational approaches for drug binding site prediction.
    Zhang Z; Li Y; Lin B; Schroeder M; Huang B
    Bioinformatics; 2011 Aug; 27(15):2083-8. PubMed ID: 21636590
    [TBL] [Abstract][Full Text] [Related]  

  • 60.
    ; ; . PubMed ID:
    [No Abstract]   [Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.