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

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196 REFERENCES Zhang, J., Gao, W., Cai, J., He, S., Zeng, R. and Chen, R. (2005). Predicting molecular formulas of fragment ions with isotope patterns in tandem mass spectra, IEEE/ACM Transactions on Computational Biology and Bioinformatics 02(3): 217–230. Zhang, X., Wei, D., Yap, Y., Li, L., Guo, S. and Chen, F. (2007). Mass spectrometry-based omics technologies in cancer diagnostics, Mass Spectrometry Reviews 26(3): 403–431. Zhang, Z., Bast, R. C., Yu, Y., Li, J., Sokoll, L. J., Rai, A. J., Rosenzweig, J. M., Cameron, B., Wang, Y. Y., Meng, X.-Y., Berchuck, A., Haaften- Day, C. V., Hacker, N. F., de Bruijn, H. W. A., van der Zee, A. G. J., Jacobs, I. J., Fung, E. T. and Chan, D. W. (2004). Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer., Cancer Res 64(16): 5882–5890. Zphel, K., Saller, B., Wunderlich, G., Grning, T., Koch, R., Wilde, J., Mann, K. and Franke, W.-G. (2003). Autoantibodies to thyroperoxidase (tpoab) in a large population of euthyroid subjects: implications for the definition of tpoab reference intervals., Clin Lab 49(11-12): 591–600.
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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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5.3. QAD GRID PLATFORM SERVER 125 F
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5.3. QAD GRID PLATFORM SERVER 127 t
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5.4. QAD GRID WORKER 129 field. A w
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5.4. QAD GRID WORKER 131 2. This re
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5.4. QAD GRID WORKER 133 Figure 5.4
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5.4. QAD GRID WORKER 135 Checkpoint
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5.4. QAD GRID WORKER 137 database b
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5.5. QAD GRID PLATFORM SERVICES 139
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5.6. QAD GRID WORKFLOWS 141 � Dat
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5.6. QAD GRID WORKFLOWS 143 Service
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Page 159 and 160: 6.2. CASE STUDIES 153 6.2 Case Stud
Page 161 and 162: 6.2. CASE STUDIES 155 Figure 6.2.2:
Page 163 and 164: 6.2. CASE STUDIES 157 MASCOT and SE
Page 165 and 166: 6.2. CASE STUDIES 159 The peak pick
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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 and 182: Appendix B Curriculum Vitae Name Ti
Page 183 and 184: References Aebersold, R. and Mann,
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: REFERENCES 195 Washburn, M. P., Wol
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