[132] D. Edwards. Non-linear normalization and background correction in one-channel cdna microarray studies. Bioinformatics, 19(7):825, 2003. [133] A. Efeyan and M. Serrano. p53: guardian <strong>of</strong> the genome and policeman <strong>of</strong> the oncogenes. Cell Cycle, 6(9):1006–1010, 2007. [134] A. J. Enright, B. John, U. Gaul, T. Tuschl, C. Sander, and D. S. Marks. MicroRNA targets in Drosophila. Genome Biol, 5(1):R1, 2003. [135] P. Eriksson, E. Perfilieva, T. Björk-Eriksson, A. Alborn, C. Nordborg, D. Peterson, and F. Gage. Neurogenesis in the adult human hippocampus. Nature medicine, 4(11):1313–1317, 1998. [136] J. Erlichman and J. Leiter. Glia modulation <strong>of</strong> the extracellular milieu as a factor in central CO2 chemosensitivity and respiratory control. Journal <strong>of</strong> Applied Physiology, 108(6):1803, 2010. [137] C. Esposito, M. Scrima, A. Carotenuto, A. Tedeschi, P. Rovero, G. D’Errico, A. Malfitano, M. Bifulco, and D. Anna Maria. Structures and micelle locations <strong>of</strong> the nonlipidated and lipidated c-terminal membrane anchor <strong>of</strong> 2’, 3’-cyclic nucleotide- 3’-phosphodiesterase. Biochemistry, 47(1):308–319, 2008. [138] S. Falcon and R. Gentleman. Using gostats to test gene lists for go term association. Bioinformatics, 23(2):257, 2007. [139] K. K. Farh, A. Grimson, C. Jan, B. P. Lewis, W. K. Johnston, L. P. Lim, C. B. Burge, and D. P. Bartel. The widespread impact <strong>of</strong> mammalian MicroRNAs on mRNA repression and evolution. Science, 310(5755):1817–21, 2005. [140] T. Fawcett, H. Eastman, J. Martindale, and N. Holbrook. Physical and functional association between gadd153 and ccaat/enhancer-binding protein beta during cellular stress. Journal <strong>of</strong> Biological Chemistry, 271(24):14285–14289, 1996. [141] C. Fears, C. Gladson, and A. Woods. Syndecan-2 is expressed in the microvasculature <strong>of</strong> gliomas and regulates angiogenic processes in microvascular endothelial cells. Journal <strong>of</strong> Biological Chemistry, 281(21):14533–14536, 2006. [142] R. Feil and F. Berger. Convergent evolution <strong>of</strong> genomic imprinting in plants and mammals. Trends in Genetics, 23(4):192–199, 2007. [143] B. G. Firehose. Broad gdac firehose. [144] A. Fischer and R. Bongini. Turning müller glia into neural progenitors in the retina. Molecular neurobiology, pages 1–11, 2010. [145] J. Flax, S. Aurora, C. Yang, C. Simonin, A. Wills, L. Billinghurst, M. Jendoubi, R. Sidman, J. Wolfe, S. Kim, et al. Engraftable human neural stem cells respond to developmental cues, replace neurons, and express foreign genes. Nature biotechnology, 16:1033–1039, 1998. [146] P. Flicek, M. Amode, D. Barrell, K. Beal, S. Brent, D. Carvalho-Silva, P. Clapham, G. Coates, S. Fairley, S. Fitzgerald, et al. Ensembl 2012. Nucleic acids research, 40(D1):D84–D90, 2012. [147] P. Flicek, M. Amode, D. Barrell, K. Beal, S. Brent, Y. Chen, P. Clapham, G. Coates, S. Fairley, S. Fitzgerald, et al. Ensembl 2011. Nucleic acids research, 39(suppl 1):D800, 2011. [148] W. Freije, F. Castro-Vargas, Z. Fang, S. Horvath, T. Cloughesy, L. Liau, P. Mischel, and S. Nelson. Gene expression pr<strong>of</strong>iling <strong>of</strong> gliomas strongly predicts survival. Cancer research, 64(18):6503, 2004. [149] R. Fricker, M. Carpenter, C. Winkler, C. Greco, M. Gates, and A. Björklund. Sitespecific migration and neuronal differentiation <strong>of</strong> human neural progenitor cells after transplantation in the adult rat brain. The Journal <strong>of</strong> neuroscience, 19(14):5990, 1999. [150] R. Friedman, K. Farh, C. Burge, and D. Bartel. Most mammalian mrnas are conserved targets <strong>of</strong> micrornas. Genome research, 19(1):92–105, 2009. [151] M. Frolov and N. Dyson. Molecular mechanisms <strong>of</strong> E2F-dependent activation and pRB-mediated repression. Journal <strong>of</strong> cell science, 117(11):2173, 2004. [152] P. Fujita, B. Rhead, A. Zweig, A. Hinrichs, D. Karolchik, M. Cline, M. Goldman, G. Barber, H. Clawson, A. Coelho, et al. The ucsc genome browser database: update 2011. Nucleic acids research, 39(suppl 1):D876, 2011.
[153] T. Fujiwara, M. Bandi, M. Nitta, E. Ivanova, R. Bronson, and D. Pellman. Cytokinesis failure generating tetraploids promotes tumorigenesis in p53-null cells. Nature, 437(7061):1043, 2005. [154] F. B. Furnari, T. Fenton, R. M. Bachoo, A. Mukasa, J. M. Stommel, A. Stegh, W. C. Hahn, K. L. Ligon, D. N. Louis, C. Brennan, L. Chin, R. A. DePinho, and W. K. Cavenee. Malignant astrocytic glioma: genetics, biology, and paths to treatment. Genes and development, 21(21):2683–710, 2007. [155] D. Gaidatzis, E. Van Nimwegen, J. Hausser, and M. Zavolan. Inference <strong>of</strong> mirna targets using evolutionary conservation and pathway analysis. BMC bioinformatics, 8(1):69, 2007. [156] R. Galli, E. Binda, U. Orfanelli, B. Cipelletti, A. Gritti, S. De Vitis, R. Fiocco, C. Foroni, F. Dimeco, and A. Vescovi. Isolation and characterization <strong>of</strong> tumorigenic, stem-like neural precursors from human glioblastoma. Cancer research, 64(19):7011, 2004. [157] G. Gallia, V. Rand, I. Siu, et al. PIK3CA gene mutations in pediatric and adult glioblastoma multiforme. Molecular cancer research, 4(10):709, 2006. [158] E. Garcia-Aragoncillo, J. Carrillo, E. Lalli, N. Agra, G. Gomez-Lopez, A. Pestana, and J. Alonso. Dax1, a direct target <strong>of</strong> ews/fli1 oncoprotein, is a principal regulator <strong>of</strong> cell-cycle progression in ewing’s tumor cells. Oncogene, 27(46):6034–6043, 2008. [159] M. Gardiner-Garden and M. Frommer. CpG islands in vertebrate genomes. Journal <strong>of</strong> molecular biology, 196(2):261–282, July 1987. [160] A. Gartel and S. Radhakrishnan. Lost in transcription: p21 repression, mechanisms, and consequences. Cancer research, 65(10):3980, 2005. [161] L. Gautier, L. Cope, B. Bolstad, and R. Irizarry. affyÂŮanalysis <strong>of</strong> affymetrix genechip data at the probe level. Bioinformatics, 20(3):307–315, 2004. [162] GBMbase. A bioinformatics resource for glioblastoma multiforme. http://beta.gbmbase.org/page/welcome/display. [163] A. Giganti, J. Plastino, B. Janji, M. Van Troys, D. Lentz, C. Ampe, C. Sykes, and E. Friederich. Actin-filament cross-linking protein t-plastin increases arp2/3-mediated actin-based movement. Journal <strong>of</strong> cell science, 118(6):1255, 2005. [164] A. Girard, R. Sachidanandam, G. J. Hannon, and M. A. Carmell. A germline-specific class <strong>of</strong> small RNAs binds mammalian Piwi proteins. Nature, 442(7099):199–202, 2006. [165] T. Glaser, S. M. Pollard, A. Smith, and O. Brüstle. Tripotential Differentiation <strong>of</strong> Adherently Expandable <strong>Neural</strong> <strong>Stem</strong> (NS) <strong>Cells</strong>. PLoS ONE, 2(3):e298, Mar. 2007. [166] V. Gocheva and J. Joyce. Cysteine cathepsins and the cutting edge <strong>of</strong> cancer invasion. Cell cycle, 6(1):60–64, 2007. [167] V. Gocheva, W. Zeng, D. Ke, D. Klimstra, T. Reinheckel, C. Peters, D. Hanahan, and J. Joyce. Distinct roles for cysteine cathepsin genes in multistage tumorigenesis. Genes & development, 20(5):543–556, 2006. [168] K. Goh, W. Poon, D. Chan, and C. Ip. Tissue plasminogen activator expression in meningiomas and glioblastomas. Clinical neurology and neurosurgery, 107(4):296–300, 2005. [169] S. Gomez-Lopez, O. Wiskow, R. Favaro, S. Nicolis, D. Price, S. Pollard, and S. A. Sox2 and pax6 maintain the proliferative and developmental potential <strong>of</strong> gliogenic neural stem cells in vitro. Glia, 59:1588–1599, 2011. [170] M. Göransson, M. Andersson, C. Forni, A. Ståhlberg, C. Andersson, A. Ol<strong>of</strong>sson, R. Mantovani, and P. Åman. The myxoid liposarcoma fus-ddit3 fusion oncoprotein deregulates nf-κb target genes by interaction with nfkbiz. Oncogene, 28(2):270–278, 2008. [171] E. Gould, A. Reeves, M. Graziano, and C. Gross. Neurogenesis in the neocortex <strong>of</strong> adult primates. Science, 286(5439):548, 1999. [172] A. Gourine and S. Kasparov. Astrocytes as brain interoceptors. Experimental Physiology, 96(4):411, 2011.
- Page 1 and 2:
Transcriptional Characterization of
- Page 3 and 4:
This dissertation is my own work an
- Page 5 and 6:
Acknowledgements I would like to th
- Page 7 and 8:
5.9 External Dataset Expression Cor
- Page 9 and 10:
Introduction 1
- Page 11 and 12:
1.1 Glial Cells in the Central Nerv
- Page 13 and 14:
1.2 Glioblastoma Multiforme Introdu
- Page 15 and 16:
1.2 Glioblastoma Multiforme Introdu
- Page 17 and 18:
1.2 Glioblastoma Multiforme Introdu
- Page 19 and 20:
1.3 Primary and Secondary Glioblast
- Page 21 and 22:
1.3 Primary and Secondary Glioblast
- Page 23 and 24:
1.3 Primary and Secondary Glioblast
- Page 25 and 26:
1.3 Primary and Secondary Glioblast
- Page 27 and 28:
1.3 Primary and Secondary Glioblast
- Page 29 and 30:
1.4 Pathways Involved in Glioblasto
- Page 31 and 32:
1.4 Pathways Involved in Glioblasto
- Page 33 and 34:
1.4 Pathways Involved in Glioblasto
- Page 35 and 36:
1.4 Pathways Involved in Glioblasto
- Page 37 and 38:
1.4 Pathways Involved in Glioblasto
- Page 39 and 40:
1.5 Pathway Crosstalk Introduction
- Page 41 and 42:
Chapter 2 Neurogenesis Contents 2.1
- Page 43 and 44:
2.1 Radial Glia Introduction VZ adj
- Page 45 and 46:
2.2 Neural Stem Cells Introduction
- Page 47 and 48:
2.2 Neural Stem Cells Introduction
- Page 49 and 50:
2.2 Neural Stem Cells Introduction
- Page 51 and 52:
2.2 Neural Stem Cells Introduction
- Page 53 and 54:
2.2 Neural Stem Cells Introduction
- Page 55 and 56:
2.2 Neural Stem Cells Introduction
- Page 57 and 58:
2.2 Neural Stem Cells Introduction
- Page 59 and 60:
2.2 Neural Stem Cells Introduction
- Page 61 and 62:
2.2 Neural Stem Cells Introduction
- Page 63 and 64:
2.2 Neural Stem Cells Introduction
- Page 65 and 66:
Chapter 3 Brain Cancer Stem Cells C
- Page 67 and 68:
3.1 The Cancer Stem Cell Hypothesis
- Page 69 and 70:
3.1 The Cancer Stem Cell Hypothesis
- Page 71 and 72:
3.2 Brain Cancer Stem Cells Introdu
- Page 73 and 74:
3.2 Brain Cancer Stem Cells Introdu
- Page 75 and 76:
3.2 Brain Cancer Stem Cells Introdu
- Page 77 and 78:
3.2 Brain Cancer Stem Cells Introdu
- Page 79 and 80:
3.2 Brain Cancer Stem Cells Introdu
- Page 81 and 82:
3.3 Glioma Culture Systems Introduc
- Page 83 and 84:
3.3 Glioma Culture Systems Introduc
- Page 85 and 86:
3.3 Glioma Culture Systems Introduc
- Page 87 and 88:
3.3 Glioma Culture Systems Introduc
- Page 89 and 90:
3.3 Glioma Culture Systems Introduc
- Page 91 and 92:
3.3 Glioma Culture Systems Introduc
- Page 93 and 94:
Chapter 4 The Non-Coding RNA World
- Page 95 and 96:
4.1 MicroRNA regulation Introductio
- Page 97 and 98:
4.1 MicroRNA regulation Introductio
- Page 99 and 100:
4.2 Target Prediction and Validatio
- Page 101 and 102:
Methods 93
- Page 103 and 104:
5.1 Tag-sequencing Data Processing
- Page 105 and 106:
5.1 Tag-sequencing Data Processing
- Page 107 and 108:
5.2 Array Comparative Genomic Hybri
- Page 109 and 110:
5.4 Quantitative Real Time-PCR Vali
- Page 111 and 112:
5.4 Quantitative Real Time-PCR Vali
- Page 113 and 114:
5.4 Quantitative Real Time-PCR Vali
- Page 115 and 116:
5.5 Literature Mining Methods Figur
- Page 117 and 118:
5.5 Literature Mining Methods How m
- Page 119 and 120:
5.6 Differential Isoform Expression
- Page 121 and 122:
5.9 External Dataset Expression Cor
- Page 123 and 124:
5.10 Glioblastoma Pathway Construct
- Page 125 and 126:
5.11 MicroRNA Target Prediction Ana
- Page 127 and 128:
Results 119
- Page 129 and 130:
6.2 Tag mapping Results Table 6.1:
- Page 131 and 132:
6.2 Tag mapping Results 123 Figure
- Page 133 and 134:
6.3 Copy Number Aberrations Results
- Page 135 and 136:
6.3 Copy Number Aberrations Results
- Page 137 and 138:
6.4 Core Differentially Expressed G
- Page 139 and 140:
6.4 Core Differentially Expressed G
- Page 141 and 142:
6.4 Core Differentially Expressed G
- Page 143 and 144:
6.4 Core Differentially Expressed G
- Page 145 and 146:
6.5 Large-scale qRT-PCR Validation
- Page 147 and 148:
6.5 Large-scale qRT-PCR Validation
- Page 149 and 150:
6.5 Large-scale qRT-PCR Validation
- Page 151 and 152:
6.6 Literature Mining for Different
- Page 153 and 154:
6.7 Isoform Differential Expression
- Page 155 and 156:
6.7 Isoform Differential Expression
- Page 157 and 158:
6.7 Isoform Differential Expression
- Page 159 and 160:
6.7 Isoform Differential Expression
- Page 161 and 162:
6.7 Isoform Differential Expression
- Page 163 and 164:
6.7 Isoform Differential Expression
- Page 165 and 166:
6.8 Long ncRNA Differential Express
- Page 167 and 168:
6.8 Long ncRNA Differential Express
- Page 169 and 170:
Chapter 7 Dataset Correlation Analy
- Page 171 and 172:
7.1 Enrichment Analysis Results Tab
- Page 173 and 174:
7.1 Enrichment Analysis Results Fig
- Page 175 and 176:
7.1 Enrichment Analysis Results Tab
- Page 177 and 178:
7.2 Glioblastoma Expression Signatu
- Page 179 and 180:
7.3 Tumour Expression Correlation R
- Page 181 and 182:
7.3 Tumour Expression Correlation R
- Page 183 and 184:
7.3 Tumour Expression Correlation R
- Page 185 and 186:
7.3 Tumour Expression Correlation R
- Page 187 and 188:
7.3 Tumour Expression Correlation R
- Page 189 and 190:
7.3 Tumour Expression Correlation R
- Page 191 and 192:
7.4 Survival Analysis Results Table
- Page 193 and 194:
7.4 Survival Analysis Results 867 g
- Page 195 and 196:
7.5 Glioblastoma Pathway Analysis R
- Page 197 and 198:
7.5 Glioblastoma Pathway Analysis R
- Page 199 and 200:
7.5 Glioblastoma Pathway Analysis R
- Page 201 and 202:
7.5 Glioblastoma Pathway Analysis R
- Page 203 and 204:
7.5 Glioblastoma Pathway Analysis R
- Page 205 and 206:
7.5 Glioblastoma Pathway Analysis R
- Page 207 and 208:
7.5 Glioblastoma Pathway Analysis R
- Page 209 and 210:
7.5 Glioblastoma Pathway Analysis R
- Page 211 and 212:
8.1 Principles Results say, this is
- Page 213 and 214:
8.3 Databases Results Figure 8.1: O
- Page 215 and 216:
8.3 Databases Results Figure 8.3: W
- Page 217 and 218:
8.4 Filters Results Bayesian method
- Page 219 and 220:
8.5 Target Prediction Ensemble Anal
- Page 221 and 222:
8.5 Target Prediction Ensemble Anal
- Page 223 and 224:
8.5 Target Prediction Ensemble Anal
- Page 225 and 226:
8.5 Target Prediction Ensemble Anal
- Page 227 and 228:
8.5 Target Prediction Ensemble Anal
- Page 229 and 230:
9.1. Digital Profiling of GNS Cell
- Page 231 and 232:
9.1. Digital Profiling of GNS Cell
- Page 233 and 234:
9.1. Digital Profiling of GNS Cell
- Page 235 and 236:
9.1. Digital Profiling of GNS Cell
- Page 237 and 238:
9.1. Digital Profiling of GNS Cell
- Page 239 and 240:
9.2. MicroRNA Target Prediction Ana
- Page 241 and 242:
9.3. Concluding Remarks Appendix pr
- Page 243 and 244:
A.1 Differential Expression Appendi
- Page 245 and 246:
A.1 Differential Expression Appendi
- Page 247 and 248:
A.1 Differential Expression Appendi
- Page 249 and 250:
A.1 Differential Expression Appendi
- Page 251 and 252:
A.1 Differential Expression Appendi
- Page 253 and 254:
A.1 Differential Expression Appendi
- Page 255 and 256:
A.1 Differential Expression Appendi
- Page 257 and 258:
A.1 Differential Expression Appendi
- Page 259 and 260:
A.2 Classified Differential Express
- Page 261 and 262:
A.2 Classified Differential Express
- Page 263 and 264:
A.2 Classified Differential Express
- Page 265 and 266:
A.3 Quantitative RT-PCR Appendix Ta
- Page 267 and 268:
A.3 Quantitative RT-PCR Appendix We
- Page 269 and 270:
A.3 Quantitative RT-PCR Appendix Ta
- Page 271 and 272:
A.3 Quantitative RT-PCR Appendix We
- Page 273 and 274:
A.4 Tag-seq vs qRT-PCR Correlation
- Page 275 and 276:
Appendix "BEX5", "DIAPH2", "GBP3",
- Page 277 and 278:
End Select End If End Sub Appendix
- Page 279 and 280: If NameStr.ToLower().Equals("query"
- Page 281 and 282: Appendix C Long ncRNAs We detected
- Page 283 and 284: C. Long ncRNAs Appendix Tag Accessi
- Page 285 and 286: D.1 Pathway Interactions Appendix F
- Page 287 and 288: D.1 Pathway Interactions Appendix F
- Page 289 and 290: D.1 Pathway Interactions Appendix F
- Page 291 and 292: D.2 Pathway Images Appendix Figure
- Page 293 and 294: D.2 Pathway Images Appendix Figure
- Page 295 and 296: E. Exon Array Data Appendix Average
- Page 297 and 298: E. Exon Array Data Appendix Average
- Page 299 and 300: E. Exon Array Data Appendix Average
- Page 301 and 302: E. Exon Array Data Appendix Average
- Page 303 and 304: E. Exon Array Data Appendix Average
- Page 305 and 306: E. Exon Array Data Appendix Average
- Page 307 and 308: E. Exon Array Data Appendix Average
- Page 309 and 310: F. MicroRNA Array Data Appendix Tab
- Page 311 and 312: F. MicroRNA Array Data Appendix GNS
- Page 313 and 314: F. MicroRNA Array Data Appendix GNS
- Page 315 and 316: Ln Natural logarithm LOH Loss of He
- Page 317 and 318: 3.3 Schematisation of cell cycle ph
- Page 319 and 320: 8.3 Workflows at the core of the pr
- Page 321 and 322: 7.1 Selected Gene Ontology terms an
- Page 323 and 324: Bibliography [1] Cell signaling tec
- Page 325 and 326: [38] G. Bain, D. Kitchens, M. Yao,
- Page 327 and 328: [78] S. Bustin, V. Benes, J. Garson
- Page 329: [112] M. Czystowska, J. Han, M. Szc
- Page 333 and 334: [192] M. Hernandez, M. Nieto, and M
- Page 335 and 336: [231] T.-M. Kim, W. Huang, R. Park,
- Page 337 and 338: [268] H. Lemjabbar-Alaoui, A. van Z
- Page 339 and 340: [305] K. MAEDA, S. MATSUHASHI, K. T
- Page 341 and 342: [342] H. Moon, M. Ahn, J. Park, K.
- Page 343 and 344: [379] D. Park and J. Rich. Biology
- Page 345 and 346: [417] P. Rakic. Guidance of neurons
- Page 347 and 348: [456] T. Shima, N. Okumura, T. Taka
- Page 349 and 350: [490] P. A. C. t’Hoen, Y. Ariyure
- Page 351 and 352: [523] T. Watanabe, A. Takeda, T. Ts