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 *

102 related articles for article (PubMed ID: 27437195)

  • 1. Prediction of protein-protein interaction sites by means of ensemble learning and weighted feature descriptor.
    Du X; Sun S; Hu C; Li X; Xia J
    J Biol Res (Thessalon); 2016 May; 23(Suppl 1):10. PubMed ID: 27437195
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. A novel feature extraction scheme for prediction of protein-protein interaction sites.
    Du X; Jing A; Hu X
    Mol Biosyst; 2015 Feb; 11(2):475-85. PubMed ID: 25413666
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Prediction of protein-protein interaction sites using an ensemble method.
    Deng L; Guan J; Dong Q; Zhou S
    BMC Bioinformatics; 2009 Dec; 10():426. PubMed ID: 20015386
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Protein-protein interaction sites prediction by ensemble random forests with synthetic minority oversampling technique.
    Wang X; Yu B; Ma A; Chen C; Liu B; Ma Q
    Bioinformatics; 2019 Jul; 35(14):2395-2402. PubMed ID: 30520961
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Hot spot prediction in protein-protein interactions by an ensemble system.
    Liu Q; Chen P; Wang B; Zhang J; Li J
    BMC Syst Biol; 2018 Dec; 12(Suppl 9):132. PubMed ID: 30598091
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. 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]  

  • 9. Prediction of protein-protein interaction sites using support vector machines.
    Koike A; Takagi T
    Protein Eng Des Sel; 2004 Feb; 17(2):165-73. PubMed ID: 15047913
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A novel feature extraction scheme with ensemble coding for protein-protein interaction prediction.
    Du X; Cheng J; Zheng T; Duan Z; Qian F
    Int J Mol Sci; 2014 Jul; 15(7):12731-49. PubMed ID: 25046746
    [TBL] [Abstract][Full Text] [Related]  

  • 11. An integration of deep learning with feature embedding for protein-protein interaction prediction.
    Yao Y; Du X; Diao Y; Zhu H
    PeerJ; 2019; 7():e7126. PubMed ID: 31245182
    [TBL] [Abstract][Full Text] [Related]  

  • 12. EL_PSSM-RT: DNA-binding residue prediction by integrating ensemble learning with PSSM Relation Transformation.
    Zhou J; Lu Q; Xu R; He Y; Wang H
    BMC Bioinformatics; 2017 Aug; 18(1):379. PubMed ID: 28851273
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A novel protein descriptor for the prediction of drug binding sites.
    Jiang M; Li Z; Bian Y; Wei Z
    BMC Bioinformatics; 2019 Sep; 20(1):478. PubMed ID: 31533611
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Fast Prediction of Protein Methylation Sites Using a Sequence-Based Feature Selection Technique.
    Wei L; Xing P; Shi G; Ji Z; Zou Q
    IEEE/ACM Trans Comput Biol Bioinform; 2019; 16(4):1264-1273. PubMed ID: 28222000
    [TBL] [Abstract][Full Text] [Related]  

  • 15. PredPhos: an ensemble framework for structure-based prediction of phosphorylation sites.
    Gao Y; Hao W; Gu J; Liu D; Fan C; Chen Z; Deng L
    J Biol Res (Thessalon); 2016 May; 23(Suppl 1):12. PubMed ID: 27437197
    [TBL] [Abstract][Full Text] [Related]  

  • 16. CFSBoost: Cumulative feature subspace boosting for drug-target interaction prediction.
    Rayhan F; Ahmed S; Md Farid D; Dehzangi A; Shatabda S
    J Theor Biol; 2019 Mar; 464():1-8. PubMed ID: 30578798
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Using Random Forest Model Combined With Gabor Feature to Predict Protein-Protein Interaction From Protein Sequence.
    Zhan XK; You ZH; Li LP; Li Y; Wang Z; Pan J
    Evol Bioinform Online; 2020; 16():1176934320934498. PubMed ID: 32655275
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. Predicting protein-RNA interaction amino acids using random forest based on submodularity subset selection.
    Pan X; Zhu L; Fan YX; Yan J
    Comput Biol Chem; 2014 Dec; 53PB():324-330. PubMed ID: 25462339
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An Improved Protein Structural Classes Prediction Method by Incorporating Both Sequence and Structure Information.
    Leyi Wei ; Minghong Liao ; Xing Gao ; Quan Zou
    IEEE Trans Nanobioscience; 2015 Jun; 14(4):339-349. PubMed ID: 25248192
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.