New Statistical Algorithms for the Analysis of Mass - FU Berlin, FB MI ...

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176 APPENDIX B. CURRICULUM VITAE
References Aebersold, R. and Mann, M. (2003). Mass spectrometry-based proteomics., Nature 422(6928): 198–207. Aittokallio, T., Nevalainen, O., Ojala, P. and Nevalainen, T. J. (2001). Automated detection of differentially expressed fragments in mRNA differential display, Electrophoresis 22(10): 1935–1045. Aldous, D. (1983). Exchangeability and related topics, Vol. 1117 of Lecture Notes in Math - Ecole d’ete de probabilites de Saint-Flour, Springer, Berlin. Allcock, W., Bester, J., Bresnahan, J., Chervenak, A., Liming, L., Meder, S. and Tuecke, S. (September 2002). Gridftp protocol specification, GGF GridFTP Working Group Document. America, A., Cordewener, J., van Geffen, M., Lommen, A., Vissers, J., Bino, R. and Hall, R. (2006). Alignment and statistical difference analysis of complex peptide data sets generated by multidimensional lc-ms, Proteomics 6: 641–653. Anderson, D. P. (2004). Boinc: a system for public-resource computing and storage, pp. 4–10. Anderson, T. W. and Darling, D. A. (1952). Asymptotic theory of certain ”goodness of fit” criteria based on stochastic processes, The Annals of Mathematical Statistics 23(2): 193–212. Anthony, D. (1996). A review of statistical methods in the journal of advanced nursing., J Adv Nurs 24(5): 1089–1094. Arkin, E. M., Chew, L. P., Huttenlocher, D. P., Kedem, K. and Mitchell, J. S. B. (1991). An efficiently computable metric for comparing polygonal shapes, IEEE Trans. Pattern Anal. Mach. Intell. 13(3): 209–216. Asadzadeh, P., Buyya, R., Kei, C., Nayar, D. and Venugopal, S. (2006). Global Grids and Software Toolkits: A Study of Four Grid Middleware Technologies, Wiley Series on Parallel and Distributed Computing, Wiley Press, New Jersey, USA, chapter 22, pp. 431–459. Baggerly, K. A., Morris, J. S., Wang, J., Gold, D., Xiao, L.-C. and Coombes, K. R. (2003). A comprehensive approach to the analysis of matrix-assisted laser desorption/ionization-time of flight proteomics spectra from serum samples., Proteomics 3(9): 1667–1672. Bakan, D. (1970). The test of significance in psychological research, Butterworth, NY. 177
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New Statistical Algorithms for the
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Contents Acknowledgments . . . . .
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New Statistical Algorithms for the
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Extended Abstract English Version M
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German Version Das Gebiet der Prote
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Chapter 1 Introduction and Survey 1
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1.2. GOALS, OBJECTIVES AND TASKS 7
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1.2. GOALS, OBJECTIVES AND TASKS 9
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Chapter 2 Preliminaries 2.1 Topic O
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2.1. TOPIC OVERVIEW 13 Figure 2.1.1
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2.1. TOPIC OVERVIEW 15 completeness
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2.2. AN EXAMPLE 17 (a) Opera A (b)
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2.2. AN EXAMPLE 19 Figure 2.2.6: Tw
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2.2. AN EXAMPLE 21 successes. We ca
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Chapter 3 Mathematical Modeling and
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3.2. INTRODUCTION TO MALDI TOF MS 2
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3.3. PREPROCESSING 31 mix (external
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3.3. PREPROCESSING 33 Figure 3.3.5:
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3.3. PREPROCESSING 35 Figure 3.3.7:
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3.4. HIGHLY SENSITIVE PEAK DETECTIO
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3.5. PEAK DETECTION IN 2D MAPS 43
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3.6. PEAK REGISTRATION (ALIGNMENT)
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3.7. IDENTIFYING POTENTIAL FEATURES
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3.8. EXTRACTING FINGERPRINTS 57 Fig
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3.8. EXTRACTING FINGERPRINTS 59 FID
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3.8. EXTRACTING FINGERPRINTS 61 Dim
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3.9. COMPLEXITY ANALYSIS 63 3.9 Com
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Chapter 4 (Bio-)Medical Application
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4.1. DATA USED 67 4.1.2 Serum Data
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4.2. STATISTICAL REMARKS 69 1. Vali
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4.2. STATISTICAL REMARKS 71 Molar v
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4.2. STATISTICAL REMARKS 73 � Fir
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4.2. STATISTICAL REMARKS 75 Let ˆ
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4.2. STATISTICAL REMARKS 77 the boo
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4.3. STUDY RESULTS 79 Figure 4.3.3:
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4.3. STUDY RESULTS 81 Figure 4.3.4:
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4.3. STUDY RESULTS 83 � kNN (gen.
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4.3. STUDY RESULTS 85 d(x, θi) =
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4.3. STUDY RESULTS 87 pairs of obje
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4.3. STUDY RESULTS 89 � “Peptid
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4.4. IDENTIFICATION OF PROTEOMIC FI
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4.6. BIOLOGICAL APPLICATIONS 101 4.
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Chapter 5 Computer Science Grid Str
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5.1. INTRODUCTION 105 � A node is
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5.1. INTRODUCTION 107 of and config
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5.1. INTRODUCTION 109 particular pr
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5.2. THE QUASI AD-HOC (QAD) GRID 11
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5.2. THE QUASI AD-HOC (QAD) GRID 11
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5.3. QAD GRID PLATFORM SERVER 115 F
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5.3. QAD GRID PLATFORM SERVER 117 j
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5.3. QAD GRID PLATFORM SERVER 119 (
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5.3. QAD GRID PLATFORM SERVER 121 p
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5.3. QAD GRID PLATFORM SERVER 123 D
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Page 141 and 142: 5.4. QAD GRID WORKER 135 Checkpoint
Page 143 and 144: 5.4. QAD GRID WORKER 137 database b
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Page 159 and 160: 6.2. CASE STUDIES 153 6.2 Case Stud
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Page 163 and 164: 6.2. CASE STUDIES 157 MASCOT and SE
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Page 169 and 170: 6.2. CASE STUDIES 163 Approach Base
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Page 173 and 174: Chapter 7 Related Work In this chap
Page 175 and 176: Chapter 8 Conclusion and Future Dir
Page 177 and 178: 8.3. FROM BIOMARKERS TO BIOPRINTS 1
Page 179 and 180: Appendix A Implementation Details T
Page 181: Appendix B Curriculum Vitae Name Ti
Page 185 and 186: REFERENCES 179 Breiman, L. (2001).
Page 187 and 188: REFERENCES 181 Downard, K. M. and M
Page 189 and 190: REFERENCES 183 Gillette, M. A., Man
Page 191 and 192: REFERENCES 185 Huyghe, E., Muller,
Page 193 and 194: REFERENCES 187 Kuijpens, J. L. P.,
Page 195 and 196: REFERENCES 189 McLachlan, S. M. and
Page 197 and 198: REFERENCES 191 Platt, J. C. (1999).
Page 199 and 200: REFERENCES 193 Stone, M. (1974). Cr
Page 201 and 202: REFERENCES 195 Washburn, M. P., Wol
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