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 *

215 related articles for article (PubMed ID: 21728988)

  • 1. Using a novel AdaBoost algorithm and Chou's Pseudo amino acid composition for predicting protein subcellular localization.
    Lin J; Wang Y
    Protein Pept Lett; 2011 Dec; 18(12):1219-25. PubMed ID: 21728988
    [TBL] [Abstract][Full Text] [Related]  

  • 2. pLoc_bal-mVirus: Predict Subcellular Localization of Multi-Label Virus Proteins by Chou's General PseAAC and IHTS Treatment to Balance Training Dataset.
    Xiao X; Cheng X; Chen G; Mao Q; Chou KC
    Med Chem; 2019; 15(5):496-509. PubMed ID: 30556503
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC.
    Zhang S; Duan X
    J Theor Biol; 2018 Jan; 437():239-250. PubMed ID: 29100918
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Predicting viral protein subcellular localization with Chou's pseudo amino acid composition and imbalance-weighted multi-label K-nearest neighbor algorithm.
    Cao JZ; Liu WQ; Gu H
    Protein Pept Lett; 2012 Nov; 19(11):1163-9. PubMed ID: 22185509
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Predicting protein subcellular location using Chou's pseudo amino acid composition and improved hybrid approach.
    Li FM; Li QZ
    Protein Pept Lett; 2008; 15(6):612-6. PubMed ID: 18680458
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Prediction of Golgi-resident protein types using general form of Chou's pseudo-amino acid compositions: Approaches with minimal redundancy maximal relevance feature selection.
    Jiao YS; Du PF
    J Theor Biol; 2016 Aug; 402():38-44. PubMed ID: 27155042
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Using the concept of Chou's pseudo amino acid composition to predict protein subcellular localization: an approach by incorporating evolutionary information and von Neumann entropies.
    Zhang SW; Zhang YL; Yang HF; Zhao CH; Pan Q
    Amino Acids; 2008 May; 34(4):565-72. PubMed ID: 18074191
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Using Chou's pseudo amino acid composition based on approximate entropy and an ensemble of AdaBoost classifiers to predict protein subnuclear location.
    Jiang X; Wei R; Zhao Y; Zhang T
    Amino Acids; 2008 May; 34(4):669-75. PubMed ID: 18256886
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A new signal characterization and signal-based Chou's PseAAC representation of protein sequences.
    Sanchez V; Peinado AM; Pérez-Córdoba JL; Gómez AM
    J Bioinform Comput Biol; 2015 Oct; 13(5):1550024. PubMed ID: 26434573
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Prediction of subcellular localization of apoptosis protein using Chou's pseudo amino acid composition.
    Lin H; Wang H; Ding H; Chen YL; Li QZ
    Acta Biotheor; 2009 Sep; 57(3):321-30. PubMed ID: 19169652
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Prediction of protein subcellular multi-localization based on the general form of Chou's pseudo amino acid composition.
    Li LQ; Zhang Y; Zou LY; Zhou Y; Zheng XQ
    Protein Pept Lett; 2012 Apr; 19(4):375-87. PubMed ID: 22185507
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Predicting subcellular localization of multi-label proteins by incorporating the sequence features into Chou's PseAAC.
    Javed F; Hayat M
    Genomics; 2019 Dec; 111(6):1325-1332. PubMed ID: 30196077
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Predicting plant protein subcellular multi-localization by Chou's PseAAC formulation based multi-label homolog knowledge transfer learning.
    Mei S
    J Theor Biol; 2012 Oct; 310():80-7. PubMed ID: 22750634
    [TBL] [Abstract][Full Text] [Related]  

  • 14. PseAAC-General: fast building various modes of general form of Chou's pseudo-amino acid composition for large-scale protein datasets.
    Du P; Gu S; Jiao Y
    Int J Mol Sci; 2014 Feb; 15(3):3495-506. PubMed ID: 24577312
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Identification of protein subcellular localization via integrating evolutionary and physicochemical information into Chou's general PseAAC.
    Shen Y; Tang J; Guo F
    J Theor Biol; 2019 Feb; 462():230-239. PubMed ID: 30452958
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Predicting protein submitochondrial locations by incorporating the pseudo-position specific scoring matrix into the general Chou's pseudo-amino acid composition.
    Qiu W; Li S; Cui X; Yu Z; Wang M; Du J; Peng Y; Yu B
    J Theor Biol; 2018 Aug; 450():86-103. PubMed ID: 29678694
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Virus-ECC-mPLoc: a multi-label predictor for predicting the subcellular localization of virus proteins with both single and multiple sites based on a general form of Chou's pseudo amino acid composition.
    Wang X; Li GZ; Lu WC
    Protein Pept Lett; 2013 Mar; 20(3):309-17. PubMed ID: 22591474
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Prediction of Protein Subcellular Localization Based on Fusion of Multi-view Features.
    Li B; Cai L; Liao B; Fu X; Bing P; Yang J
    Molecules; 2019 Mar; 24(5):. PubMed ID: 30845684
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Prediction of protein subcellular localization by incorporating multiobjective PSO-based feature subset selection into the general form of Chou's PseAAC.
    Mandal M; Mukhopadhyay A; Maulik U
    Med Biol Eng Comput; 2015 Apr; 53(4):331-44. PubMed ID: 25564182
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Predict protein structural class by incorporating two different modes of evolutionary information into Chou's general pseudo amino acid composition.
    Liang Y; Zhang S
    J Mol Graph Model; 2017 Nov; 78():110-117. PubMed ID: 29055184
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.