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New approaches to identification of bacterial pathogens by surface enhanced laser desorption/ionization time of flight mass spectrometry in concert with artificial neural networks, with special reference to Neisseria gonorrhoeae

, , , , and . Journal of Medical Microbiology, 54 (Pt 12): 1205--1211 (December 2005)PMID: 16278435.
DOI: 10.1099/jmm.0.46223-0

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New approaches to identification of bacterial pathogens by surface enhanced laser desorption/ionization time of flight mass spectrometry in concert with artificial neural networks, with special reference to Neisseria gonorrhoeae, , , , and . Journal of Medical Microbiology, 54 (Pt 12): 1205--1211 (December 2005)PMID: 16278435.Exploration of ovarian cancer micro array data focus on gene expression patterns relevant to survival using artificial neural networks., , , , and . IWBBIO, page 116-123. Copicentro Editorial, (2014)A quantifier-based fuzzy classification system for breast cancer patients., , , , , , , and . Artif. Intell. Medicine, 58 (3): 175-184 (2013)An introduction to artificial neural networks in bioinformatics - application to complex microarray and mass spectrometry datasets in cancer studies., , and . Briefings Bioinform., 10 (3): 315-329 (2009)Utilizing Artificial Neural Networks to Elucidate Serum Biomarker Patterns Which Discriminate Between Clinical Stages in Melanoma., , , , , and . CIBCB, page 455-460. IEEE, (2005)Classification of bacterial species from proteomic data using combinatorial approaches incorporating artificial neural networks, cluster analysis and principal components analysis., , , and . Bioinform., 21 (10): 2191-2199 (2005)Selecting Lung Cancer Patients from UK Primary Care Data: A Longitudinal Study of Feature Trends., , , , , , , , and . AII, page 43-59. (2021)Estrogen receptor status prediction for breast cancer using artificial neural network., , and . ICMLC, page 727-731. IEEE, (2011)Artificial Neural Network Based Algorithm for Biomolecular Interactions Modeling., , , and . IWANN (1), volume 5517 of Lecture Notes in Computer Science, page 877-885. Springer, (2009)Pattern recognition of multidimensional PBMC flow cytometry histograms for prostate cancer identification., and . IWBBIO, page 509-516. Copicentro Editorial, (2013)