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 *

213 related articles for article (PubMed ID: 25984606)

  • 1. 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]  

  • 2. 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]  

  • 3. Predicting protein-protein interactions from primary protein sequences using a novel multi-scale local feature representation scheme and the random forest.
    You ZH; Chan KC; Hu P
    PLoS One; 2015; 10(5):e0125811. PubMed ID: 25946106
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Accurate prediction of protein-protein interactions by integrating potential evolutionary information embedded in PSSM profile and discriminative vector machine classifier.
    Li ZW; You ZH; Chen X; Li LP; Huang DS; Yan GY; Nie R; Huang YA
    Oncotarget; 2017 Apr; 8(14):23638-23649. PubMed ID: 28423569
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Sequence-based prediction of protein-protein interactions using weighted sparse representation model combined with global encoding.
    Huang YA; You ZH; Chen X; Chan K; Luo X
    BMC Bioinformatics; 2016 Apr; 17(1):184. PubMed ID: 27112932
    [TBL] [Abstract][Full Text] [Related]  

  • 6. RVMAB: Using the Relevance Vector Machine Model Combined with Average Blocks to Predict the Interactions of Proteins from Protein Sequences.
    An JY; You ZH; Meng FR; Xu SJ; Wang Y
    Int J Mol Sci; 2016 May; 17(5):. PubMed ID: 27213337
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Predicting protein-protein interactions by fusing various Chou's pseudo components and using wavelet denoising approach.
    Tian B; Wu X; Chen C; Qiu W; Ma Q; Yu B
    J Theor Biol; 2019 Feb; 462():329-346. PubMed ID: 30452960
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. 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]  

  • 10. PCVMZM: Using the Probabilistic Classification Vector Machines Model Combined with a Zernike Moments Descriptor to Predict Protein-Protein Interactions from Protein Sequences.
    Wang Y; You Z; Li X; Chen X; Jiang T; Zhang J
    Int J Mol Sci; 2017 May; 18(5):. PubMed ID: 28492483
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Prediction of Protein-Protein Interactions from Amino Acid Sequences Based on Continuous and Discrete Wavelet Transform Features.
    Wang T; Li L; Huang YA; Zhang H; Ma Y; Zhou X
    Molecules; 2018 Apr; 23(4):. PubMed ID: 29617272
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Detecting protein-protein interactions with a novel matrix-based protein sequence representation and support vector machines.
    You ZH; Li J; Gao X; He Z; Zhu L; Lei YK; Ji Z
    Biomed Res Int; 2015; 2015():867516. PubMed ID: 26000305
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis.
    You ZH; Lei YK; Zhu L; Xia J; Wang B
    BMC Bioinformatics; 2013; 14 Suppl 8(Suppl 8):S10. PubMed ID: 23815620
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Protein-Protein Interactions Prediction Based on Graph Energy and Protein Sequence Information.
    Xu D; Xu H; Zhang Y; Chen W; Gao R
    Molecules; 2020 Apr; 25(8):. PubMed ID: 32316294
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences.
    Wang J; Zhang L; Jia L; Ren Y; Yu G
    Int J Mol Sci; 2017 Nov; 18(11):. PubMed ID: 29117139
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. Global protein-protein interaction networks in yeast saccharomyces cerevisiae and helicobacter pylori.
    Zandi F; Mansouri P; Goodarzi M
    Talanta; 2023 Dec; 265():124836. PubMed ID: 37393709
    [TBL] [Abstract][Full Text] [Related]  

  • 18. iHSP-PseRAAAC: Identifying the heat shock protein families using pseudo reduced amino acid alphabet composition.
    Feng PM; Chen W; Lin H; Chou KC
    Anal Biochem; 2013 Nov; 442(1):118-25. PubMed ID: 23756733
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Detection of Interactions between Proteins by Using Legendre Moments Descriptor to Extract Discriminatory Information Embedded in PSSM.
    Wang YB; You ZH; Li LP; Huang YA; Yi HC
    Molecules; 2017 Aug; 22(8):. PubMed ID: 28820478
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Using Weighted Sparse Representation Model Combined with Discrete Cosine Transformation to Predict Protein-Protein Interactions from Protein Sequence.
    Huang YA; You ZH; Gao X; Wong L; Wang L
    Biomed Res Int; 2015; 2015():902198. PubMed ID: 26634213
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.