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69 related items for PubMed ID: 16610948

  • 1. Gene expression profile of empirically delineated classes of unexplained chronic fatigue.
    Carmel L, Efroni S, White PD, Aslakson E, Vollmer-Conna U, Rajeevan MS.
    Pharmacogenomics; 2006 Apr; 7(3):375-86. PubMed ID: 16610948
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  • 2. Polymorphisms in genes regulating the HPA axis associated with empirically delineated classes of unexplained chronic fatigue.
    Smith AK, White PD, Aslakson E, Vollmer-Conna U, Rajeevan MS.
    Pharmacogenomics; 2006 Apr; 7(3):387-94. PubMed ID: 16610949
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  • 3. The validity of an empirical delineation of heterogeneity in chronic unexplained fatigue.
    Aslakson E, Vollmer-Conna U, White PD.
    Pharmacogenomics; 2006 Apr; 7(3):365-73. PubMed ID: 16610947
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  • 7. Gene expression correlates of unexplained fatigue.
    Whistler T, Taylor R, Craddock RC, Broderick G, Klimas N, Unger ER.
    Pharmacogenomics; 2006 Apr; 7(3):395-405. PubMed ID: 16610950
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  • 8. Linear data mining the Wichita clinical matrix suggests sleep and allostatic load involvement in chronic fatigue syndrome.
    Gurbaxani BM, Jones JF, Goertzel BN, Maloney EM.
    Pharmacogenomics; 2006 Apr; 7(3):455-65. PubMed ID: 16610955
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  • 9. Identifying illness parameters in fatiguing syndromes using classical projection methods.
    Broderick G, Craddock RC, Whistler T, Taylor R, Klimas N, Unger ER.
    Pharmacogenomics; 2006 Apr; 7(3):407-19. PubMed ID: 16610951
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  • 10. The challenge of integrating disparate high-content data: epidemiological, clinical and laboratory data collected during an in-hospital study of chronic fatigue syndrome.
    Vernon SD, Reeves WC.
    Pharmacogenomics; 2006 Apr; 7(3):345-54. PubMed ID: 16610945
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  • 11. Seven genomic subtypes of chronic fatigue syndrome/myalgic encephalomyelitis: a detailed analysis of gene networks and clinical phenotypes.
    Kerr JR, Burke B, Petty R, Gough J, Fear D, Mattey DL, Axford JS, Dalgleish AG, Nutt DJ.
    J Clin Pathol; 2008 Jun; 61(6):730-9. PubMed ID: 18057078
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  • 12. A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays.
    McLachlan GJ, Bean RW, Jones LB.
    Bioinformatics; 2006 Jul 01; 22(13):1608-15. PubMed ID: 16632494
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  • 16. [Identification and application of marker genes for differential diagnosis of chronic fatigue syndrome].
    Kawai T, Rokutan K.
    Nihon Rinsho; 2007 Jun 01; 65(6):1029-33. PubMed ID: 17561693
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  • 17. Graph-based consensus clustering for class discovery from gene expression data.
    Yu Z, Wong HS, Wang H.
    Bioinformatics; 2007 Nov 01; 23(21):2888-96. PubMed ID: 17872912
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  • 19. New gene selection method for multiclass tumor classification by class centroid.
    Shen Q, Shi WM, Kong W.
    J Biomed Inform; 2009 Feb 01; 42(1):59-65. PubMed ID: 18835752
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  • 20. Multiclass cancer classification by support vector machines with class-wise optimized genes and probability estimates.
    Anand A, Suganthan PN.
    J Theor Biol; 2009 Aug 07; 259(3):533-40. PubMed ID: 19406131
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