Revealing metabolite biomarkers for acupuncture treatment by linear programming based feature selection
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Chen Chen | Xiang-Sun Zhang | Yong Wang | Ling-Yun Wu | Qiao-Feng Wu | Xian-Zhong Yan | Fan-Rong Liang | ShuGuang Yu | Ling-Yun Wu | Yong Wang | F. Liang | Xian-Zhong Yan | Qiao-feng Wu | Shuguang Yu | Cheng Chen | Xiang-Sun Zhang
[1] Ilya Levner. Proteomic Pattern Recognition , 2004 .
[2] E Holmes,et al. NMR and pattern recognition studies on the time-related metabolic effects of alpha-naphthylisothiocyanate on liver, urine, and plasma in the rat: an integrative metabonomic approach. , 2001, Chemical research in toxicology.
[3] Luonan Chen,et al. Optimization meets systems biology , 2010, BMC Systems Biology.
[4] B. Kramer,et al. Trends in biomarker research for cancer detection. , 2001, The Lancet. Oncology.
[5] Elaine Holmes,et al. A metabonomic investigation of hepatotoxicity using diffusion-edited 1H NMR spectroscopy of blood serum. , 2003, The Analyst.
[6] Ashutosh Kumar Singh,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2010 .
[7] Trupti Joshi,et al. Inferring gene regulatory networks from multiple microarray datasets , 2006, Bioinform..
[8] E Holmes,et al. Development of a model for classification of toxin‐induced lesions using 1H NMR spectroscopy of urine combined with pattern recognition , 1998, NMR in biomedicine.
[9] I. Wilson,et al. Physiological variation in metabolic phenotyping and functional genomic studies: use of orthogonal signal correction and PLS‐DA , 2002, FEBS letters.
[10] Luonan Chen,et al. Biomolecular Networks: Methods and Applications in Systems Biology , 2009 .
[11] Edoardo Amaldi,et al. On the Approximability of Minimizing Nonzero Variables or Unsatisfied Relations in Linear Systems , 1998, Theor. Comput. Sci..
[12] Sui Huang,et al. Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles , 2003, Bioinform..
[13] Chen Chen,et al. Identifying biomarkers for acupuncture treatment via an optimization model , 2011, 2011 IEEE International Conference on Systems Biology (ISB).
[14] Liang Fan-rong. Metabonomics and Pattern Recognition Study on the Specificity of Foot-Yangming Meridian Points , 2010 .
[15] G. Dienel,et al. Glucose and lactate metabolism during brain activation , 2001, Journal of neuroscience research.
[16] Xuegong Zhang,et al. Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data , 2006, BMC Bioinformatics.
[17] Lawrence Carin,et al. Joint Classifier and Feature Optimization for Comprehensive Cancer Diagnosis Using Gene Expression Data , 2004, J. Comput. Biol..
[18] J. Lindon,et al. NMR‐based metabonomic approaches for evaluating physiological influences on biofluid composition , 2005, NMR in biomedicine.
[19] Henrik Antti,et al. Application of orthogonal signal correction to minimise the effects of physical and biological variation in high resolution 1H NMR spectra of biofluids. , 2002, The Analyst.
[20] Aixia Guo,et al. Gene Selection for Cancer Classification using Support Vector Machines , 2014 .
[21] Qin Chen,et al. 1H NMR-based metabonomic study on the metabolic changes in the plasma of patients with functional dyspepsia and the effect of acupuncture. , 2010, Journal of pharmaceutical and biomedical analysis.
[22] Charles S. Johnson,et al. An Improved Diffusion-Ordered Spectroscopy Experiment Incorporating Bipolar-Gradient Pulses , 1995 .
[23] Alexander J. Hartemink,et al. Finding Diagnostic Biomarkers in Proteomic Spectra , 2006, Pacific Symposium on Biocomputing.
[24] Yong Wang,et al. A Linear Programming Framework for Inferring Gene Regulatory Networks by Integrating Heterogeneous Data , 2010 .
[25] X. Cui,et al. Statistical tests for differential expression in cDNA microarray experiments , 2003, Genome Biology.
[26] K. Briski,et al. Lactate is a critical "sensed" variable in caudal hindbrain monitoring of CNS metabolic stasis. , 2005, American journal of physiology. Regulatory, integrative and comparative physiology.
[27] F. Azuaje,et al. Multiple SVM-RFE for gene selection in cancer classification with expression data , 2005, IEEE Transactions on NanoBioscience.
[28] J. Sims,et al. The mechanism of acupuncture analgesia: a review , 1997 .
[29] Lawrence Carin,et al. Sparse multinomial logistic regression: fast algorithms and generalization bounds , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[30] M. Castro,et al. A metabolic switch in brain: glucose and lactate metabolism modulation by ascorbic acid , 2009, Journal of neurochemistry.
[31] V. Routh,et al. Differential effects of glucose and lactate on glucosensing neurons in the ventromedial hypothalamic nucleus. , 2005, Diabetes.
[32] J. B. Rosen,et al. Lower Dimensional Representation of Text Data Based on Centroids and Least Squares , 2003 .
[33] Silvia Mangia,et al. The in vivo neuron‐to‐astrocyte lactate shuttle in human brain: evidence from modeling of measured lactate levels during visual stimulation , 2009, Journal of neurochemistry.
[34] U. Tan,et al. THE MECHANISM OF ACUPUNCTURE AND CLINICAL APPLICATIONS , 2006, The International journal of neuroscience.
[35] M. Cipolla,et al. Mechanical signaling through connective tissue: a mechanism for the therapeutic effect of acupuncture , 2001, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.
[36] T. Ebbels,et al. Improved analysis of multivariate data by variable stability scaling: application to NMR-based metabolic profiling , 2003 .
[37] Isabelle Guyon,et al. An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..
[38] Robert Tibshirani,et al. A comparison of fold-change and the t-statistic for microarray data analysis , 2007 .