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Volumn , Issue , 2007, Pages

SOM-based peptide prototyping for mass spectrometry peak intensity prediction

Author keywords

Local linear map; Maldi MS; Peak intensity prediction; Self Organizing Map

Indexed keywords

IDENTIFICATION OF PROTEINS; LEARNING ARCHITECTURES; LOCAL LINEAR; MALDI-MS; MOLECULAR FEATURE; PEAK INTENSITY; REGRESSION FUNCTION; SUPPORT VECTOR REGRESSION (SVR);

EID: 84893483286     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (3)

References (9)
  • 1
    • 0742305695 scopus 로고    scopus 로고
    • Intensity-based protein identification by machine learning from a library of tandem mass spectra
    • Feb
    • J. E Elias, F. D Gibbons, O. D King, F. P Roth, and S. P Gygi. Intensity-based protein identification by machine learning from a library of tandem mass spectra. Nat Biotechnol, 22(2):214-219, Feb 2004.
    • (2004) Nat Biotechnol , vol.22 , Issue.2 , pp. 214-219
    • Elias, J.E.1    Gibbons, F.D.2    King, O.D.3    Roth, F.P.4    Gygi, S.P.5
  • 2
    • 0036808751 scopus 로고    scopus 로고
    • Peptide mass fingerprinting peak intensity prediction: Extracting knowledge from spectra
    • Oct
    • S. Gay, P.-A. Binz, D. F Hochstrasser, and R. D Appel. Peptide mass fingerprinting peak intensity prediction: extracting knowledge from spectra. Proteomics, 2(10):1374-1391, Oct 2002.
    • (2002) Proteomics , vol.2 , Issue.10 , pp. 1374-1391
    • Gay, S.1    Binz, P.-A.2    Hochstrasser, D.F.3    Appel, R.D.4
  • 4
    • 0020068152 scopus 로고
    • Self-organized formation of topo-logically correct feature maps
    • T. Kohonen. Self-organized formation of topo-logically correct feature maps. In Biological Cybernetics, Volume 43, pages 59-69, 1982.
    • (1982) Biological Cybernetics , vol.43 , pp. 59-69
    • Kohonen, T.1
  • 5
    • 0027632248 scopus 로고
    • 'Neural gas' network for vector quantization and its application to time-series prediction
    • T. M. Martinetz, S. G Berkovich, and K. J. Schulten. 'neural gas' network for vector quantization and its application to time-series prediction. In IEEE Trans. Neural Networks, Volume 4, pages 558-569, 1993.
    • (1993) IEEE Trans. Neural Networks , vol.4 , pp. 558-569
    • Martinetz, T.M.1    Berkovich, S.G.2    Schulten, K.J.3
  • 6
    • 0000232749 scopus 로고
    • Learning with the self-organizing map
    • T. Kohonen et al., editor Amsterdam Elsevier Science Publishers
    • Helge Ritter. Learning with the self-organizing map. In T. Kohonen et al., editor, Artificial Neural Networks, pages 379-384, Amsterdam, 1991. Elsevier Science Publishers.
    • (1991) Artificial Neural Networks , pp. 379-384
    • Ritter, H.1
  • 7
    • 27744497057 scopus 로고    scopus 로고
    • Protein and peptide identification algorithms using MS for use in high-throughput, automated pipelines
    • Nov
    • I. Shadforth, D. Crowther, and C. Bessant. Protein and peptide identification algorithms using MS for use in high-throughput, automated pipelines. Proteomics, 5(16):4082-4095, Nov 2005.
    • (2005) Proteomics , vol.5 , Issue.16 , pp. 4082-4095
    • Shadforth, I.1    Crowther, D.2    Bessant, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.