SUMMARY OF ALGORITHMIC FRAGMENTS FOR STATISTICAL IDENTIFICATION OF MARKERS FROM A SET OF SPECTRAL COURSES
Authors:
Jiří Knížek 1; Ladislav Beránek 2; Petr Bouchal 3,4; Bořivoj Vojtěšek 4; Rudolf Nenutil 4; Pavel Tomšík 5
Authors‘ workplace:
Department of Medical Biophysics, Faculty of Medicine in Hradec Kralove, Charles University in Prague, Czech Republic
1; Department of Applied Mathematics, University of South Bohemia, Czech Republic
2; Department of Biochemistry, Faculty of Science, Masaryk University, Czech Republic
3; Regional Centre for Applied Molecular Oncology, Masaryk Memorial Cancer Institute, Czech Republic
4; Department of Medical Biochemistry, Faculty of Medicine in Hradec Kralove, Charles University in Prague, Czech Republic
5
Published in:
Lékař a technika - Clinician and Technology No. 3, 2013, 43, 30-35
Category:
Original research
Overview
A brief introduction of algorithms for the statistical identification of markers from a set of spectral courses is the topic of our paper. Partial results, demonstrated by pictures, are very promising. Therefore, our next effort will be directed at the construction of the 1st prototype of some semi-commercial software for the identification of markers from a set of spectral courses.
Keywords:
marker, biomarker, regression, tests of hypotheses, software
Sources
[1] Arnoldi, W. E. The principle of minimized iteration in the solution of the matrix eigenvalue problem. Quart. Appl. Math., 1951, vol. 9, p. 17-29.
[2] Ciphergen® Biosystems, Inc. (2002) ProteinChip software 3.1. Operation Manual.
[3] Cohen, J. Statistical Power Analysis for the Behavioral Science. Mahwah, New Persey: Lawrence Erlbaum, 1988, 2nd ed., p.567.
[4] Daly, L.E., Bourke, G.J. Interpretation and Uses of Medical Statistics. Oxford: Blackwell Science, 2000, 5th ed., p. 276-279.
[5] Forsythe G. E. Generation and Use of Orthogonal Polynomials for Data-fitting on a Digital Computer, J. Soc. Indust. Appl. Math., 1957, Vol. 5, p. 74-88.
[6] Gatignon, H. Statistical Analysis of Management Data. Kluwer Academic Publishers (New York, Boston, Dordrecht, London, Moscow), 2003.
[7] Gautschi, W. Orthogonal polynomials: computation and approxima-tion. Numerical Mathematics and Scientific Computation. Oxford Science Publications. Oxford University Press, New York, 2004.
[8] Giraud, L., Langou, J., Rozloznik, M., On the loss of orthogonality in the Gram-Schmidt orthogonalization process. Computers & Mathematics with Applications, 2005, Vol. 50, p. 1069–1075.
[9] Giraud, L., Langou, J., Rozloznik, M., van den Eshof, J. Rounding error analysis of the classical Gram-Schmidt orthogonalization process. Numer. Math., 2005, Vol. 101, p. 87-100.
[10] Higham, N. J. Accuracy and stability of numerical algorithms. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, 2002, 2nd ed.
[11] Holcakova, J., Hernychova, L., Bouchal, P., Brozkova, K., Zaloudik, J., Valik, D., Nenutil, R., Vojtesek, B. Identification of alphaB-crystallin, a biomarker of renal cell carcinoma by SELDI-TOF MS, The International Journal of Biological Markers, Italy: Wichtig editore, 2008, Vol. 23, no. 1, p. 48-53. ISSN 0393-6155.
[12] Judge, G. G, Griffiths, W. E, Hill, R. C, Lutkepohl, H., Tsoung-Chao, L. The Theory and Practice of Econometrics, New York: J. Wiley, 2005.
[13] Knizek, J. Marker Statistics I.: Regression analysis of dependences in medicine and molecular biology, VDM Publishing House Ltd., Mauritius, 2011, ISBN-NR.: 978-3-639-33015-1.
[14] Knizek, J, Sindelar J, Beranek L, Vojtesek B, Nenutil R, Brozkova K, Drazan V, Hubalek M & Kubacek L. Power function for tests of null hypotheses on mutual linear regression functions’ relations, International Journal of Applied Mathematics & Statistics, 2008, Vol. 2, no. S08; p. 26-33.
[15] Knizek, J, Sindelar J, Vojtesek B, Bouchal P, Nenutil R & Beranek L. Identification of Markers by Simultaneous Tests in a Set of Quantifying Dependences, International Journal of Statistics & Economics, 2010, Vol. 5 [Special], no. A10, p. 12-20.
[16] Knizek, J, Sindelar J, Vojtesek B, Bouchal P, Nenutil R, Beranek L & Dedik O. Using Markers to Aid Decision Making in Diagnostics, International Journal of Tomography & Statistics, 2011, Vol. 16, no. W11, p. 41-55.
[17] Knizek, J, Sindelar, J, Pulpan, Z, Vojtesek, B, Nenutil, R, Brozkova, K, Drazan, V, Hubalek, M & Beranek, L, Test of the Hypothesis That One Group of Dependences is Consistent with Another Group of Dependences, International Journal of Ap-plied Mathematics & Statistics, 2008, Vol. 2, no. A08, p. 2-18.
[18] Knizek, J, Tichy P, Beranek L, Sindelar J, Vojtesek B, Bouchal P, Nenutil R & Dedik, O. Note on Generating Orthogonal Polynomials and Their Application in Solving Complicated Polynomial Regression Tasks, International Journal of Mathematics and Computation, 2010, Vol. 7, no. J10, p. 48-60.
[19] Ralston, A. A First Course in Numerical Analysis, McGraw Hill Book Company, New York, 1973.
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2013 Issue 3
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