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 *

114 related articles for article (PubMed ID: 26717407)

  • 21. Robust and accurate prediction of protein self-interactions from amino acids sequence using evolutionary information.
    An JY; You ZH; Chen X; Huang DS; Yan G; Wang DF
    Mol Biosyst; 2016 Nov; 12(12):3702-3710. PubMed ID: 27759121
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Predicting protein-protein interactions from protein sequences by a stacked sparse autoencoder deep neural network.
    Wang YB; You ZH; Li X; Jiang TH; Chen X; Zhou X; Wang L
    Mol Biosyst; 2017 Jun; 13(7):1336-1344. PubMed ID: 28604872
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Prediction of protein-protein interactions from amino acid sequences using a novel multi-scale continuous and discontinuous feature set.
    You ZH; Zhu L; Zheng CH; Yu HJ; Deng SP; Ji Z
    BMC Bioinformatics; 2014; 15 Suppl 15(Suppl 15):S9. PubMed ID: 25474679
    [TBL] [Abstract][Full Text] [Related]  

  • 24. LMPID: a manually curated database of linear motifs mediating protein-protein interactions.
    Sarkar D; Jana T; Saha S
    Database (Oxford); 2015; 2015():. PubMed ID: 25776024
    [TBL] [Abstract][Full Text] [Related]  

  • 25. 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]  

  • 26. ppiPre: predicting protein-protein interactions by combining heterogeneous features.
    Deng Y; Gao L; Wang B
    BMC Syst Biol; 2013; 7 Suppl 2(Suppl 2):S8. PubMed ID: 24565177
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.
    Zhang SB; Tang QR
    J Theor Biol; 2016 Jul; 401():30-7. PubMed ID: 27117309
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Computationally predicting protein-RNA interactions using only positive and unlabeled examples.
    Cheng Z; Zhou S; Guan J
    J Bioinform Comput Biol; 2015 Jun; 13(3):1541005. PubMed ID: 25790785
    [TBL] [Abstract][Full Text] [Related]  

  • 29. EcID. A database for the inference of functional interactions in E. coli.
    Andres Leon E; Ezkurdia I; GarcĂ­a B; Valencia A; Juan D
    Nucleic Acids Res; 2009 Jan; 37(Database issue):D629-35. PubMed ID: 19004873
    [TBL] [Abstract][Full Text] [Related]  

  • 30. A machine learning based method for the prediction of secretory proteins using amino acid composition, their order and similarity-search.
    Garg A; Raghava GP
    In Silico Biol; 2008; 8(2):129-40. PubMed ID: 18928201
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Prediction of protein-protein interactions with clustered amino acids and weighted sparse representation.
    Huang Q; You Z; Zhang X; Zhou Y
    Int J Mol Sci; 2015 May; 16(5):10855-69. PubMed ID: 25984606
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Unraveling the conundrum of seemingly discordant protein-protein interaction datasets.
    Gupta S; Wallqvist A; Bondugula R; Ivanic J; Reifman J
    Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():783-6. PubMed ID: 21096109
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Improved protein-protein interactions prediction via weighted sparse representation model combining continuous wavelet descriptor and PseAA composition.
    Huang YA; You ZH; Chen X; Yan GY
    BMC Syst Biol; 2016 Dec; 10(Suppl 4):120. PubMed ID: 28155718
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Using machine learning techniques and genomic/proteomic information from known databases for defining relevant features for PPI classification.
    Urquiza JM; Rojas I; Pomares H; Herrera J; Florido JP; Valenzuela O; Cepero M
    Comput Biol Med; 2012 Jun; 42(6):639-50. PubMed ID: 22575173
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Using discriminative vector machine model with 2DPCA to predict interactions among proteins.
    Li Z; Nie R; You Z; Cao C; Li J
    BMC Bioinformatics; 2019 Dec; 20(Suppl 25):694. PubMed ID: 31874626
    [TBL] [Abstract][Full Text] [Related]  

  • 36. InPrePPI: an integrated evaluation method based on genomic context for predicting protein-protein interactions in prokaryotic genomes.
    Sun J; Sun Y; Ding G; Liu Q; Wang C; He Y; Shi T; Li Y; Zhao Z
    BMC Bioinformatics; 2007 Oct; 8():414. PubMed ID: 17963500
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Prediction of anti-inflammatory proteins/peptides: an insilico approach.
    Gupta S; Sharma AK; Shastri V; Madhu MK; Sharma VK
    J Transl Med; 2017 Jan; 15(1):7. PubMed ID: 28057002
    [TBL] [Abstract][Full Text] [Related]  

  • 38. ProfPPIdb: Pairs of physical protein-protein interactions predicted for entire proteomes.
    Tran L; Hamp T; Rost B
    PLoS One; 2018; 13(7):e0199988. PubMed ID: 30020956
    [TBL] [Abstract][Full Text] [Related]  

  • 39. An improved method for identification of small non-coding RNAs in bacteria using support vector machine.
    Barman RK; Mukhopadhyay A; Das S
    Sci Rep; 2017 Apr; 7():46070. PubMed ID: 28383059
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Sequence-based prediction of protein protein interaction using a deep-learning algorithm.
    Sun T; Zhou B; Lai L; Pei J
    BMC Bioinformatics; 2017 May; 18(1):277. PubMed ID: 28545462
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 6.