메뉴 건너뛰기




Volumn , Issue , 2006, Pages 541-548

Machine learning and soft-computing in bioinformatics - A short journey

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOINFORMATICS; COMPUTATION THEORY; DIAGNOSIS; FUZZY LOGIC; MASS SPECTROMETRY; SOFT COMPUTING;

EID: 84887001987     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1142/9789812774118_0077     Document Type: Conference Paper
Times cited : (4)

References (48)
  • 1
  • 2
    • 33745751254 scopus 로고    scopus 로고
    • Theoretical and Experimental DNA Computation
    • Springer, Berlin
    • M. Amos. Theoretical and Experimental DNA Computation. Natural Computing. Springer, Berlin, 2005.
    • (2005) Natural Computing
    • Amos, M.1
  • 3
    • 0036161259 scopus 로고    scopus 로고
    • Gene selection for cancer classification using support vector machines
    • J. Guyon, J. Weston, S. Barnhill, and V. Vapnik. Gene selection for cancer classification using support vector machines. Mach. Learn., 46:389-422, 2002.
    • (2002) Mach. Learn , vol.46 , pp. 389-422
    • Guyon, J.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 5
    • 0037246661 scopus 로고    scopus 로고
    • Wavelets in bioinformatics and computational biology: State of art and perspectives
    • Pietro Lio. Wavelets in bioinformatics and computational biology: state of art and perspectives. Bioinjormatics, 19(1):2-9, 2003.
    • (2003) Bioinjormatics , vol.19 , Issue.1 , pp. 2-9
    • Lio, P.1
  • 6
  • 10
    • 38149005270 scopus 로고    scopus 로고
    • Peak intensity prediction for prnf mass spectra using support vector regression
    • W. Timm, S. Boecker, T. Twellmann, and T. W. Nattkemper. Peak intensity prediction for prnf mass spectra using support vector regression. In Proc. of FLINS 2006, 2006.
    • (2006) Proc. of FLINS 2006
    • Timm, W.1    Boecker, S.2    Twellmann, T.3    Nattkemper, T.W.4
  • 11
    • 84961989055 scopus 로고    scopus 로고
    • Relevanzlernen und statistische Diskriminanzverfahren zur ICD-10 Klassifizierung von SCL90-Patienten-Profilen bei Therapiebeginn
    • In G. Plöttner, editor, Leipziger Universitätsverlag, Leipzig, Germany
    • T. Villmann, G. Blaser, A. Körner, and C. Albani. Relevanzlernen und statistische Diskriminanzverfahren zur ICD-10 Klassifizierung von SCL90-Patienten-Profilen bei Therapiebeginn. In G. Plöttner, editor, Aktuelle Entwicklungen in der Psychotherapieforschung, pages 99-118. Leipziger Universitätsverlag, Leipzig, Germany, 2004.
    • (2004) Aktuelle Entwicklungen in Der Psychotherapieforschung , pp. 99-118
    • Villmann, T.1    Blaser, G.2    Körner, A.3    Albani, C.4
  • 16
    • 0027632248 scopus 로고
    • Neural-gas’ network for vector quantization and its application to time-series prediction
    • Thomas M. Martinetz, Stanislav G. Berkovich, and Klaus J. Schulten. ’Neural-gas’ network for vector quantization and its application to time-series prediction. IEEE Trans. on Neural Networks, 4(4):558-569,1993.
    • (1993) IEEE Trans. on Neural Networks , vol.4 , Issue.4 , pp. 558-569
    • Martinetz, T.M.1    Berkovich, S.G.2    Schulten, K.J.3
  • 18
    • 33644899424 scopus 로고    scopus 로고
    • Magnification control in self-organizing maps and neural gas
    • February
    • T. Villmann and J.-C. Claussen. Magnification control in self-organizing maps and neural gas. Neural Computation, 18(2):446-469, February 2006.
    • (2006) Neural Computation , vol.18 , Issue.2 , pp. 446-469
    • Villmann, T.1    Claussen, J.-C.2
  • 19
    • 85026190757 scopus 로고    scopus 로고
    • Feature scoring by mutual information for classification of mass spectra
    • C. Krier, D. Francois, V. Wertz, and M. Verleysen. Feature scoring by mutual information for classification of mass spectra. In Proc. of FLINS 2006, 2006.
    • (2006) Proc. of FLINS , pp. 2006
    • Krier, C.1    Francois, D.2    Wertz, V.3    Verleysen, M.4
  • 20
    • 0344541989 scopus 로고    scopus 로고
    • Applications of the growing self-organizing map
    • Th. Villmann and H.-U. Bauer. Applications of the growing self-organizing map. Neurocomputing, 21(1-3):91-100,1998.
    • (1998) Neurocomputing , vol.21 , Issue.1-3 , pp. 91-100
    • Villmann, T.H.1    Bauer, H.-U.2
  • 22
    • 19344369995 scopus 로고    scopus 로고
    • Nir and mass spectra classification: Bayesian methods for wavelet-based feature selection
    • Marina Vannucci, Naijun Sha, and Philip J. Brown. Nir and mass spectra classification: Bayesian methods for wavelet-based feature selection. Chemometrics and Int. Lab. Systems, 77:139-148, 2005.
    • (2005) Chemometrics and Int. Lab. Systems , vol.77 , pp. 139-148
    • Vannucci, M.1    Sha, N.2    Brown, P.J.3
  • 23
    • 0141855285 scopus 로고    scopus 로고
    • Decision tree classification of proteins identified by mass spectrometry of blood serum samples from people with and without lung cancer
    • M.K. Mareky, G.D. Tourassi, and C.E. Floyd Jr. Decision tree classification of proteins identified by mass spectrometry of blood serum samples from people with and without lung cancer. Proteomics, 3:1678-1679, 2003.
    • (2003) Proteomics , vol.3 , pp. 1678-1679
    • Mareky, M.K.1    Tourassi, G.D.2    Floyd, C.E.3
  • 25
    • 0031042985 scopus 로고    scopus 로고
    • Phylogenetic reconstruction using an unsupervised growing neural network that adopts the topology of a phylogenetic tree
    • J. Dopazo and J.M. Carazo. Phylogenetic reconstruction using an unsupervised growing neural network that adopts the topology of a phylogenetic tree. Journal of Molecular· Evolution, 44(2):226-233, 1997.
    • (1997) Journal of Molecular· Evolution , vol.44 , Issue.2 , pp. 226-233
    • Dopazo, J.1    Carazo, J.M.2
  • 30
    • 85156210800 scopus 로고    scopus 로고
    • Generalized learning vector quantization
    • In D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo, editors, MIT Press, Cambridge, MA, USA
    • A. Sato and K. Yamada. Generalized learning vector quantization. In D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo, editors, Advances in Neural Information Processing Systems 8. Proceedings of the 1995 Conference, pages 423-9. MIT Press, Cambridge, MA, USA, 1996.
    • (1996) Advances in Neural Information Processing Systems 8. Proceedings of the 1995 Conference , pp. 423-429
    • Sato, A.1    Yamada, K.2
  • 31
  • 33
    • 33845571066 scopus 로고    scopus 로고
    • Analysis and visualization of proteomic data by fuzzy labeled self-organizing maps
    • page in press. IEEE Computer Society Press, Los Alamitos
    • F.-M. Schleif, T. Elssner, M. Kostrzewa, T. Villmann, and B. Hammer. Analysis and visualization of proteomic data by fuzzy labeled self-organizing maps. In Proc. of CBMS, page in press. IEEE Computer Society Press, Los Alamitos, 2006.
    • (2006) Proc. of CBMS
    • Schleif, F.-M.1    Elssner, T.2    Kostrzewa, M.3    Villmann, T.4    Hammer, B.5
  • 36
    • 18544384330 scopus 로고    scopus 로고
    • Prototype based recognition of splice sites
    • U. Seiffert, L.A. Jain, and P. Schweitzer, editors, Springer-Verlag
    • Barbara Hammer, Marc Strickert, and Thomas Villmann. Prototype based recognition of splice sites. In U. Seiffert, L.A. Jain, and P. Schweitzer, editors, Bioinformatic using Computational Intelligence Paradigms, pages 25-56. Springer-Verlag, 2005.
    • (2005) Bioinformatic Using Computational Intelligence Paradigms , pp. 25-56
    • Hammer, B.1    Strickert, M.2    Villmann, T.3
  • 37
    • 32544451159 scopus 로고    scopus 로고
    • Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis
    • March 2006. ISSN: 0925-2312
    • M. Strickert, U. Seiffert, N. Sreenivasulu, W. Weschke, T. Villmann, and B. Hammer. Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis. Neurocomputing, 69(6-7):651-659, March 2006. ISSN: 0925-2312.
    • Neurocomputing , vol.69 , Issue.6-7 , pp. 651-659
    • Strickert, M.1    Seiffert, U.2    Sreenivasulu, N.3    Weschke, W.4    Villmann, T.5    Hammer, B.6
  • 38
    • 0006008365 scopus 로고    scopus 로고
    • SOM-based exploratory analysis of gene expression data
    • In Nigel Allinson, Hujun Yin, Lesley Allinson, and Jon Slack, editors, Springer, London
    • Samuel Kaski. SOM-based exploratory analysis of gene expression data. In Nigel Allinson, Hujun Yin, Lesley Allinson, and Jon Slack, editors, Advances in Self-Organizing Maps, pages 124-131. Springer, London, 2001.
    • (2001) Advances in Self-Organizing Maps , pp. 124-131
    • Kaski, S.1
  • 39
    • 2442536791 scopus 로고    scopus 로고
    • Dissimilarity learning for nominal data
    • V. Cheng, C.-H. Li, J.T. Kwok, and C.-K. Li. Dissimilarity learning for nominal data. Pattern Recognition, 37(7):1471-1477, 2004.
    • (2004) Pattern Recognition , vol.37 , Issue.7 , pp. 1471-1477
    • Cheng, V.1    Li, C.-H.2    Kwok, J.T.3    Li, C.-K.4
  • 41
    • 0037379640 scopus 로고    scopus 로고
    • Neural maps in remote sensing image analysis
    • Th. Villmann, E. Merémyi, and B. Hammer. Neural maps in remote sensing image analysis. Neural Networks, 16(3-4):389-403, 2003.
    • (2003) Neural Networks , vol.16 , Issue.3-4 , pp. 389-403
    • Villmann, T.H.1    Merémyi, E.2    Hammer, B.3
  • 45
    • 0034894278 scopus 로고    scopus 로고
    • PAL: An object-oriented programming library for molecular evolution and phylogenetics
    • A. Drummond and K. Strimmer. PAL: an object-oriented programming library for molecular evolution and phylogenetics. Bioinformatics Applications Note, 17(7):662-663, 200l.
    • (2001) Bioinformatics Applications Note , vol.17 , Issue.7 , pp. 662-663
    • Drummond, A.1    Strimmer, K.2
  • 46
    • 85036474865 scopus 로고    scopus 로고
    • IKP Stuttgart MHH Hannover and Bruker Daltonik Leipzig. internal results on leukaemia
    • IKP Stuttgart MHH Hannover and Bruker Daltonik Leipzig. internal results on leukaemia, 2004.
    • (2004)
  • 47
    • 0036645099 scopus 로고    scopus 로고
    • Serum protein finger printing coupled with a patternmatching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men
    • July
    • B.L. Adam et al. Serum protein finger printing coupled with a patternmatching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men. Cancer Research, 62(13):3609-3614, July 2002.
    • (2002) Cancer Research , vol.62 , Issue.13 , pp. 3609-3614
    • Adam, B.L.1
  • 48
    • 67650219527 scopus 로고    scopus 로고
    • Magnetic bead based human plasma profiling discriminate acute lymphatic leukaemia from non-diseased samples
    • E. Schaffeler, U. Zanger, and M. Schwab. Magnetic bead based human plasma profiling discriminate acute lymphatic leukaemia from non-diseased samples. In 52st ASMS Conf. 2004, page TPV 420, 2004.
    • (2004) 52St ASMS Conf. 2004 , pp. 420
    • Schaffeler, E.1    Zanger, U.2    Schwab, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.