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 *

150 related articles for article (PubMed ID: 25048512)

  • 21. Multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery.
    Han H; Li XL
    BMC Bioinformatics; 2011 Feb; 12 Suppl 1(Suppl 1):S7. PubMed ID: 21342590
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Gene selection for microarray cancer classification using a new evolutionary method employing artificial intelligence concepts.
    Dashtban M; Balafar M
    Genomics; 2017 Mar; 109(2):91-107. PubMed ID: 28159597
    [TBL] [Abstract][Full Text] [Related]  

  • 23. A novel feature selection approach for biomedical data classification.
    Peng Y; Wu Z; Jiang J
    J Biomed Inform; 2010 Feb; 43(1):15-23. PubMed ID: 19647098
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Gene expression data classification using locally linear discriminant embedding.
    Li B; Zheng CH; Huang DS; Zhang L; Han K
    Comput Biol Med; 2010 Oct; 40(10):802-10. PubMed ID: 20864095
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Feature selection and tumor classification for microarray data using relaxed Lasso and generalized multi-class support vector machine.
    Kang C; Huo Y; Xin L; Tian B; Yu B
    J Theor Biol; 2019 Feb; 463():77-91. PubMed ID: 30537483
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.
    Alshamlan HM; Badr GH; Alohali YA
    Comput Biol Chem; 2015 Jun; 56():49-60. PubMed ID: 25880524
    [TBL] [Abstract][Full Text] [Related]  

  • 27. New variable selection method using interval segmentation purity with application to blockwise kernel transform support vector machine classification of high-dimensional microarray data.
    Tang LJ; Du W; Fu HY; Jiang JH; Wu HL; Shen GL; Yu RQ
    J Chem Inf Model; 2009 Aug; 49(8):2002-9. PubMed ID: 19645418
    [TBL] [Abstract][Full Text] [Related]  

  • 28. A kernel-based clustering method for gene selection with gene expression data.
    Chen H; Zhang Y; Gutman I
    J Biomed Inform; 2016 Aug; 62():12-20. PubMed ID: 27215190
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Gene features selection for three-class disease classification via multiple orthogonal partial least square discriminant analysis and S-plot using microarray data.
    Yang M; Li X; Li Z; Ou Z; Liu M; Liu S; Li X; Yang S
    PLoS One; 2013; 8(12):e84253. PubMed ID: 24386356
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Stable feature selection and classification algorithms for multiclass microarray data.
    Student S; Fujarewicz K
    Biol Direct; 2012 Oct; 7():33. PubMed ID: 23031190
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Gene selection algorithms for microarray data based on least squares support vector machine.
    Tang EK; Suganthan PN; Yao X
    BMC Bioinformatics; 2006 Feb; 7():95. PubMed ID: 16504159
    [TBL] [Abstract][Full Text] [Related]  

  • 32. An experimental comparison of feature selection methods on two-class biomedical datasets.
    Drotár P; Gazda J; Smékal Z
    Comput Biol Med; 2015 Nov; 66():1-10. PubMed ID: 26327447
    [TBL] [Abstract][Full Text] [Related]  

  • 33. A two-stage hybrid biomarker selection method based on ensemble filter and binary differential evolution incorporating binary African vultures optimization.
    Li W; Chi Y; Yu K; Xie W
    BMC Bioinformatics; 2023 Apr; 24(1):130. PubMed ID: 37016297
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Variable selection using probability density function similarity for support vector machine classification of high-dimensional microarray data.
    Tang LJ; Jiang JH; Wu HL; Shen GL; Yu RQ
    Talanta; 2009 Jul; 79(2):260-7. PubMed ID: 19559875
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Application of genetic algorithms and constructive neural networks for the analysis of microarray cancer data.
    Luque-Baena RM; Urda D; Subirats JL; Franco L; Jerez JM
    Theor Biol Med Model; 2014 May; 11 Suppl 1(Suppl 1):S7. PubMed ID: 25077572
    [TBL] [Abstract][Full Text] [Related]  

  • 36. A multiple kernel support vector machine scheme for feature selection and rule extraction from gene expression data of cancer tissue.
    Chen Z; Li J; Wei L
    Artif Intell Med; 2007 Oct; 41(2):161-75. PubMed ID: 17851055
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.
    Hajiloo M; Rabiee HR; Anooshahpour M
    BMC Bioinformatics; 2013; 14 Suppl 13(Suppl 13):S4. PubMed ID: 24266942
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Feature weight estimation for gene selection: a local hyperlinear learning approach.
    Cai H; Ruan P; Ng M; Akutsu T
    BMC Bioinformatics; 2014 Mar; 15():70. PubMed ID: 24625071
    [TBL] [Abstract][Full Text] [Related]  

  • 39. R-HEFS: Rough set based heterogeneous ensemble feature selection method for medical data classification.
    Bania RK; Halder A
    Artif Intell Med; 2021 Apr; 114():102049. PubMed ID: 33875164
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Filter versus wrapper gene selection approaches in DNA microarray domains.
    Inza I; Larrañaga P; Blanco R; Cerrolaza AJ
    Artif Intell Med; 2004 Jun; 31(2):91-103. PubMed ID: 15219288
    [TBL] [Abstract][Full Text] [Related]  

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