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Volumn 6, Issue , 2000, Pages 3542-3545

Modelling electropherogram data for DNA sequencing using variable dimension MCMC

Author keywords

[No Author keywords available]

Indexed keywords

DNA; DNA SEQUENCES; GENE ENCODING; BIOCHEMISTRY; ELECTRIC FIELD EFFECTS; FREQUENCY DOMAIN ANALYSIS; MATHEMATICAL MODELS; SIGNAL PROCESSING;

EID: 0033677986     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2000.860166     Document Type: Conference Paper
Times cited : (15)

References (15)
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    • Andrieu, C.1    Doucet, A.2
  • 3
    • 0029971394 scopus 로고    scopus 로고
    • A graph theoretic approach to the analysis of DNA sequencing data
    • A. J. Bemo. A graph theoretic approach to the analysis of DNA sequencing data. Genome Research, 6:80-91, 1996.
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    • Bemo, A.J.1
  • 4
    • 0031955518 scopus 로고    scopus 로고
    • Base-calling of automated sequencer traces using Phred. I. Accuracy Assessment
    • B. Ewing, L. Hillier, M. Wendl, and P. Green. Base-calling of automated sequencer traces using Phred. I. Accuracy Assessment. Genome Research, 8:175-185, 1998.
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    • Ewing, B.1    Hillier, L.2    Wendl, M.3    Green, P.4
  • 5
    • 0021518209 scopus 로고
    • Stochastic Relaxation, Gibbs distributions, and the Bayesian restoration of images
    • S. Geman and D. Geman. Stochastic Relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Trans. Pan. Anal, and Mach. Int., 6(6):721-741, 1984.
    • (1984) IEEE Trans. Pan. Anal, and Mach. Int. , vol.6 , Issue.6 , pp. 721-741
    • Geman, S.1    Geman, D.2
  • 6
    • 0027442961 scopus 로고    scopus 로고
    • An adaptive object oriented strategy for base calling in DNA sequence analysis
    • 93
    • M. Giddings et al. An adaptive object oriented strategy for base calling in DNA sequence analysis. Nucleic Acids Research, 21(19):4530-4540, 93.
    • Nucleic Acids Research , vol.21 , Issue.19 , pp. 4530-4540
    • Giddings, M.1
  • 8
    • 77956889087 scopus 로고
    • Reversible Jump Markov Chain Monte Carlo computation and Bayesian model determination
    • P. J. Green. Reversible Jump Markov Chain Monte Carlo computation and Bayesian model determination. Biometrika, 82(4):711-732, 1995.
    • (1995) Biometrika , vol.82 , Issue.4 , pp. 711-732
    • Green, P.J.1
  • 9
    • 77956890234 scopus 로고
    • Monte Carlo sampling methods using Markov Chains and their applications
    • W. Hastings. Monte Carlo sampling methods using Markov Chains and their applications. Biometrika, 57(1):97-109, 1970.
    • (1970) Biometrika , vol.57 , Issue.1 , pp. 97-109
    • Hastings, W.1
  • 12
    • 18244378520 scopus 로고    scopus 로고
    • On Bayesian analysis of mixtures with an unknown number of components (with discussion)
    • S. Richardson and P. J. Green. On Bayesian analysis of mixtures with an unknown number of components (with discussion). J. Roy. Slat. Soc. Series B, 59(4):731-758, 1997.
    • (1997) J. Roy. Slat. Soc. Series B , vol.59 , Issue.4 , pp. 731-758
    • Richardson, S.1    Green, P.J.2
  • 13
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    • DNA sequencing with chain-terminating inhibitors
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  • 14
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    • A Reversible Jump sampler for autoregressive time series
    • P. T. Troughton and S. J. Godsill. A Reversible Jump sampler for autoregressive time series. In Proceedings of IEEE ICASSP, volume IV, pages 2257-2260, 1998.
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    • Troughton, P.T.1    Godsill, S.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.