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Volumn 56, Issue 4, 2010, Pages 741-749

Robust early pregnancy prediction of later preeclampsia using metabolomic biomarkers

Author keywords

biomarkers; hypertension; metabolomics; preeclampsia; screening

Indexed keywords

BIOLOGICAL MARKER;

EID: 77957240409     PISSN: 0194911X     EISSN: None     Source Type: Journal    
DOI: 10.1161/HYPERTENSIONAHA.110.157297     Document Type: Article
Times cited : (242)

References (38)
  • 1
    • 14644412849 scopus 로고    scopus 로고
    • Pre-eclampsia
    • DOI 10.1016/S0140-6736(05)17987-2
    • Sibai B, Dekker G, Kupferminc M. Pre-eclampsia. Lancet. 2005;365: 785-799. (Pubitemid 40311367)
    • (2005) Lancet , vol.365 , Issue.9461 , pp. 785-799
    • Sibai, B.1    Dekker, G.2    Kupferminc, M.3
  • 2
    • 36348944504 scopus 로고    scopus 로고
    • Pre-eclampsia and risk of cardiovascular disease and cancer in later life: Systematic review and meta-analysis
    • DOI 10.1136/bmj.39335.385301.BE
    • Bellamy L, Casas JP, Hingorani AD, Williams DJ. Pre-eclampsia and risk of cardiovascular disease and cancer in later life: systematic review and meta-analysis. BMJ. 2007;335:974. (Pubitemid 350144670)
    • (2007) British Medical Journal , vol.335 , Issue.7627 , pp. 974-977
    • Bellamy, L.1    Casas, J.-P.2    Hingorani, A.D.3    Williams, D.J.4
  • 4
    • 20444409135 scopus 로고    scopus 로고
    • Latest advances in understanding preeclampsia
    • Redman CW, Sargent IL. Latest advances in understanding preeclampsia. Science. 2005;308:1592-1594.
    • (2005) Science , vol.308 , pp. 1592-1594
    • Redman, C.W.1    Sargent, I.L.2
  • 9
    • 0038598345 scopus 로고    scopus 로고
    • Evolutionary computation for the interpretation of metabolome data
    • Harrigan GG, Goodacre R, eds Boston, MA: Kluwer Academic Publishers
    • Goodacre R, Kell DB. Evolutionary computation for the interpretation of metabolome data. In: Harrigan GG, Goodacre R, eds. Metabolic Profiling: Its Role in Biomarker Discovery and Gene Function. Boston, MA: Kluwer Academic Publishers; 2003:239-256.
    • (2003) Metabolic Profiling: Its Role in Biomarker Discovery and Gene Function , pp. 239-256
    • Goodacre, R.1    Kell, D.B.2
  • 13
    • 33644963733 scopus 로고    scopus 로고
    • Novel biomarkers for pre-eclampsia detected using metabolomics and machine learning
    • Kenny L, Dunn W, Ellis D, Myers J, Baker P, Consortium G, Kell D. Novel biomarkers for pre-eclampsia detected using metabolomics and machine learning. Metabolomics. 2005;1:227-234.
    • (2005) Metabolomics , vol.1 , pp. 227-234
    • Kenny, L.1    Dunn, W.2    Ellis, D.3    Myers, J.4    Baker, P.5    Consortium, G.6    Kell, D.7
  • 15
    • 33846240326 scopus 로고    scopus 로고
    • Statistical strategies for avoiding false discoveries in metabolomics and related experiments
    • Broadhurst DI, Kell DB. Statistical strategies for avoiding false discoveries in metabolomics and related experiments. Metabolomics. 2006; 2:171-196.
    • (2006) Metabolomics , vol.2 , pp. 171-196
    • Broadhurst, D.I.1    Kell, D.B.2
  • 18
    • 32444446805 scopus 로고    scopus 로고
    • XCMS: Processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification
    • DOI 10.1021/ac051437y
    • Smith CA, Want EJ, OMaille G, Abagyan R, Siuzdak G. Xcms: Processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal Chem. 2006;78: 779-787. (Pubitemid 43228585)
    • (2006) Analytical Chemistry , vol.78 , Issue.3 , pp. 779-787
    • Smith, C.A.1    Want, E.J.2    O'Maille, G.3    Abagyan, R.4    Siuzdak, G.5
  • 20
    • 0002692783 scopus 로고
    • Soft modelling by latent variables: The non-linear iterative partial least squares (nipals) approach
    • Gani J, ed London, United Kingdom: Academic Press
    • Wold H. Soft modelling by latent variables: the non-linear iterative partial least squares (nipals) approach. In: Gani J, ed. Perspectives in Probability and Statistics, Papers in Honour of M. S. Bartlett. London, United Kingdom: Academic Press; 1975:117-142.
    • (1975) Perspectives in Probability and Statistics, Papers in Honour of M. S. Bartlett , pp. 117-142
    • Wold, H.1
  • 26
    • 16244366026 scopus 로고
    • Index for rating diagnostic tests
    • Youden WJ. Index for rating diagnostic tests. Cancer. 1950;3:32-35.
    • (1950) Cancer , vol.3 , pp. 32-35
    • Youden, W.J.1
  • 27
    • 33645311528 scopus 로고    scopus 로고
    • The inconsistency of "optimal" cutpoints obtained using two criteria based on the receiver operating characteristic curve
    • Perkins NJ, Schisterman EF. The inconsistency of "optimal" cutpoints obtained using two criteria based on the receiver operating characteristic curve. Am J Epidemiol. 2006;163:670-675.
    • (2006) Am J Epidemiol , vol.163 , pp. 670-675
    • Perkins, N.J.1    Schisterman, E.F.2
  • 28
    • 0030859519 scopus 로고    scopus 로고
    • Genetic algorithms as a method for variable selection in multiple linear regression and partial least squares regression, with applications to pyrolysis mass spectrometry
    • Broadhurst D, Goodacre R, Jones A, Rowland JJ, Kell DB. Genetic algorithms as a method for variable selection in multiple linear regression and partial least squares regression, with applications to pyrolysis mass spectrometry. Analytica Chimica Acta. 1997;348:71-86.
    • (1997) Analytica Chimica Acta. , vol.348 , pp. 71-86
    • Broadhurst, D.1    Goodacre, R.2    Jones, A.3    Rowland, J.J.4    Kell, D.B.5
  • 30
    • 0038699591 scopus 로고    scopus 로고
    • High-throughput classification of yeast mutants for functional genomics using metabolic footprinting
    • DOI 10.1038/nbt823
    • Allen J, Davey HM, Broadhurst D, Heald JK, Rowland JJ, Oliver SG, Kell DB. High-throughput classification of yeast mutants for functional genomics using metabolic footprinting. Nat Biotechnol. 2003;21: 692-696. (Pubitemid 36638098)
    • (2003) Nature Biotechnology , vol.21 , Issue.6 , pp. 692-696
    • Allen, J.1    Davey, H.M.2    Broadhurst, D.3    Heald, J.K.4    Rowland, J.J.5    Oliver, S.G.6    Kell, D.B.7
  • 31
    • 16444371874 scopus 로고    scopus 로고
    • Genetic algorithm optimization for pre-processing and variable selection of spectroscopic data
    • DOI 10.1093/bioinformatics/bti102
    • Jarvis RM, Goodacre R. Genetic algorithm optimization for preprocessing and variable selection of spectroscopic data. Bioinformatics. 2005;21:860-868. (Pubitemid 40476056)
    • (2005) Bioinformatics , vol.21 , Issue.7 , pp. 860-868
    • Jarvis, R.M.1    Goodacre, R.2
  • 32
    • 0036042222 scopus 로고    scopus 로고
    • Metabolomics and machine learning: Explanatory analysis of complex metabolome data using genetic programming to produce simple, robust rules
    • Kell DB. Metabolomics and machine learning: explanatory analysis of complex metabolome data using genetic programming to produce simple, robust rules. Mol Biol Rep. 2002;29:237-241.
    • (2002) Mol Biol Rep , vol.29 , pp. 237-241
    • Kell, D.B.1
  • 35
    • 0345743608 scopus 로고    scopus 로고
    • Here is the evidence, now what is the hypothesis? the complementary roles of inductive and hypothesis-driven science in the post-genomic era
    • Kell DB, Oliver SG. Here is the evidence, now what is the hypothesis? The complementary roles of inductive and hypothesis-driven science in the post-genomic era. Bioessays. 2004;26:99-105.
    • (2004) Bioessays , vol.26 , pp. 99-105
    • Kell, D.B.1    Oliver, S.G.2
  • 36
    • 72149089567 scopus 로고    scopus 로고
    • Maternal serum placental protein 13 at 11-13 weeks of gestation in preeclampsia
    • Akolekar R, Syngelaki A, Beta J, Kocylowski R, Nicolaides KH. Maternal serum placental protein 13 at 11-13 weeks of gestation in preeclampsia. Prenat Diagn. 2009;29:1103-1108.
    • (2009) Prenat Diagn , vol.29 , pp. 1103-1108
    • Akolekar, R.1    Syngelaki, A.2    Beta, J.3    Kocylowski, R.4    Nicolaides, K.H.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.