Transcriptional Characterization of Glioma Neural Stem Cells Diva ...

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8.5 Target Prediction Ensemble Analysis Results Prediction algorithms involved in the combination set E-score ElMMo miRanda PITA PicTar5 PicTar6 TargetscanS 0.3087 PITA PicTar6 0.3086 Diana-microT miRBase PITA PicTar5 PicTar6 0.3086 ElMMo miRBase miRanda PITA PicTar5 TargetscanS 0.3086 Diana-microT miRBase PicTar5 0.3085 ElMMo miRBase miRanda PicTar5 PicTar6 0.3085 PITA TargetscanS 0.3085 Diana-microT miRBase PITA PicTar5 TargetscanS 0.3085 Diana-microT miRBase PicTar6 TargetscanS 0.3085 Diana-microT PicTar5 PicTar6 TargetscanS 0.3085 ElMMo miRBase miRanda PITA PicTar5 PicTar6 TargetscanS 0.3085 ElMMo miRBase miRanda PicTar5 TargetscanS 0.3084 PITA PicTar6 TargetscanS 0.3083 Diana-microT miRBase PITA PicTar5 PicTar6 TargetscanS 0.3083 miRBase PITA 0.3082 PITA PicTar5 0.3082 ElMMo miRBase miRanda PicTar5 PicTar6 TargetscanS 0.3082 miRBase PITA PicTar6 0.3081 Diana-microT miRBase PicTar5 PicTar6 0.3080 PITA PicTar5 PicTar6 0.3080 miRBase PITA TargetscanS 0.3080 Diana-microT miRBase PicTar5 TargetscanS 0.3080 PITA PicTar5 TargetscanS 0.3080 miRBase PITA PicTar6 TargetscanS 0.3079 PITA PicTar5 PicTar6 TargetscanS 0.3079 Diana-microT miRBase PicTar5 PicTar6 TargetscanS 0.3078 miRBase PITA PicTar5 0.3077 miRBase PITA PicTar5 TargetscanS 0.3076 miRBase PITA PicTar5 PicTar6 0.3075 miRBase PITA PicTar5 PicTar6 TargetscanS 0.3075 TargetscanS 0.3073 Diana-microT miRanda PITA TargetscanS 0.3071 Diana-microT miRanda PITA 0.3070 Diana-microT miRanda PITA PicTar6 TargetscanS 0.3070 Diana-microT miRanda PITA PicTar6 0.3069 Diana-microT miRBase miRanda PITA TargetscanS 0.3068 Diana-microT miRanda PITA PicTar5 TargetscanS 0.3068 PicTar6 TargetscanS 0.3068 Diana-microT miRBase miRanda PITA 0.3067 Diana-microT miRanda PITA PicTar5 0.3067 Diana-microT miRBase miRanda PITA PicTar6 0.3067 Diana-microT miRBase miRanda PITA PicTar6 TargetscanS 0.3067 Diana-microT miRanda PITA PicTar5 PicTar6 TargetscanS 0.3067 Diana-microT miRanda PITA PicTar5 PicTar6 0.3066 Diana-microT miRBase miRanda PITA PicTar5 TargetscanS 0.3066 Diana-microT miRBase miRanda PITA PicTar5 0.3065 Diana-microT miRBase miRanda PITA PicTar5 PicTar6 TargetscanS 0.3065 Diana-microT miRBase miRanda PITA PicTar5 PicTar6 0.3064 miRanda PITA TargetscanS 0.3060 miRanda PITA PicTar6 TargetscanS 0.3060 miRBase TargetscanS 0.3059 miRanda PITA 0.3058 miRBase miRanda PITA TargetscanS 0.3058 PicTar5 TargetscanS 0.3058 miRanda PITA PicTar5 TargetscanS 0.3058 miRanda PITA PicTar6 0.3057 miRBase miRanda PITA PicTar6 TargetscanS 0.3057 miRanda PITA PicTar5 PicTar6 TargetscanS 0.3057 miRBase miRanda PITA PicTar5 TargetscanS 0.3056 miRBase PicTar6 TargetscanS 0.3056 miRBase miRanda PITA 0.3055 miRanda PITA PicTar5 0.3055 PicTar5 PicTar6 TargetscanS 0.3055 miRBase miRanda PITA PicTar5 PicTar6 TargetscanS 0.3055 miRBase miRanda PITA PicTar6 0.3054 miRanda PITA PicTar5 PicTar6 0.3054 Diana-microT miRanda TargetscanS 0.3053 miRBase miRanda PITA PicTar5 0.3052 miRBase miRanda PITA PicTar5 PicTar6 0.3052 Diana-microT miRanda PicTar6 TargetscanS 0.3052 Diana-microT miRBase miRanda TargetscanS 0.3050 miRBase PicTar5 TargetscanS 0.3049 Diana-microT miRanda PicTar5 TargetscanS 0.3049 Diana-microT miRBase miRanda PicTar6 TargetscanS 0.3049 218
8.5 Target Prediction Ensemble Analysis Results Prediction algorithms involved in the combination set E-score Diana-microT miRanda PicTar5 PicTar6 TargetscanS 0.3049 Diana-microT miRBase miRanda PicTar5 TargetscanS 0.3047 miRBase PicTar5 PicTar6 TargetscanS 0.3047 Diana-microT miRBase miRanda PicTar5 PicTar6 TargetscanS 0.3046 Diana-microT miRanda 0.3045 Diana-microT miRanda PicTar6 0.3044 Diana-microT miRBase miRanda 0.3041 Diana-microT miRanda PicTar5 0.3040 Diana-microT miRBase miRanda PicTar6 0.3040 Diana-microT miRanda PicTar5 PicTar6 0.3039 Diana-microT miRBase miRanda PicTar5 0.3037 Diana-microT miRBase miRanda PicTar5 PicTar6 0.3037 PicTar6 0.3020 miRanda TargetscanS 0.3020 miRanda PicTar6 TargetscanS 0.3020 miRBase miRanda TargetscanS 0.3019 miRBase miRanda PicTar6 TargetscanS 0.3019 miRanda PicTar5 TargetscanS 0.3018 miRanda PicTar5 PicTar6 TargetscanS 0.3018 miRBase miRanda PicTar5 TargetscanS 0.3017 miRBase miRanda PicTar5 PicTar6 TargetscanS 0.3017 miRBase PicTar6 0.3011 miRBase 0.3008 miRBase PicTar5 PicTar6 0.3003 miRBase PicTar5 0.3000 PicTar5 PicTar6 0.2999 PicTar5 0.2989 miRBase miRanda PicTar5 PicTar6 0.2987 miRBase miRanda PicTar6 0.2986 miRBase miRanda PicTar5 0.2985 miRBase miRanda 0.2984 miRanda PicTar5 PicTar6 0.2983 miRanda PicTar6 0.2982 miRanda PicTar5 0.2981 miRanda 0.2979 219
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Transcriptional Characterization of
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This dissertation is my own work an
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Acknowledgements I would like to th
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5.9 External Dataset Expression Cor
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Introduction 1
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1.1 Glial Cells in the Central Nerv
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1.2 Glioblastoma Multiforme Introdu
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1.3 Primary and Secondary Glioblast
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1.4 Pathways Involved in Glioblasto
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1.5 Pathway Crosstalk Introduction
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Chapter 2 Neurogenesis Contents 2.1
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2.1 Radial Glia Introduction VZ adj
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2.2 Neural Stem Cells Introduction
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Chapter 3 Brain Cancer Stem Cells C
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3.1 The Cancer Stem Cell Hypothesis
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3.1 The Cancer Stem Cell Hypothesis
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3.2 Brain Cancer Stem Cells Introdu
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3.3 Glioma Culture Systems Introduc
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Chapter 4 The Non-Coding RNA World
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4.1 MicroRNA regulation Introductio
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4.1 MicroRNA regulation Introductio
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4.2 Target Prediction and Validatio
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Methods 93
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5.1 Tag-sequencing Data Processing
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5.1 Tag-sequencing Data Processing
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5.2 Array Comparative Genomic Hybri
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5.4 Quantitative Real Time-PCR Vali
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5.5 Literature Mining Methods Figur
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5.5 Literature Mining Methods How m
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5.6 Differential Isoform Expression
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5.9 External Dataset Expression Cor
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5.10 Glioblastoma Pathway Construct
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5.11 MicroRNA Target Prediction Ana
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Results 119
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6.2 Tag mapping Results Table 6.1:
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6.2 Tag mapping Results 123 Figure
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6.3 Copy Number Aberrations Results
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6.3 Copy Number Aberrations Results
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6.4 Core Differentially Expressed G
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6.5 Large-scale qRT-PCR Validation
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6.6 Literature Mining for Different
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6.7 Isoform Differential Expression
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6.8 Long ncRNA Differential Express
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6.8 Long ncRNA Differential Express
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Chapter 7 Dataset Correlation Analy
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7.1 Enrichment Analysis Results Tab
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7.1 Enrichment Analysis Results Fig
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Page 217 and 218: 8.4 Filters Results Bayesian method
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Page 241 and 242: 9.3. Concluding Remarks Appendix pr
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End Select End If End Sub Appendix
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If NameStr.ToLower().Equals("query"
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Appendix C Long ncRNAs We detected
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C. Long ncRNAs Appendix Tag Accessi
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D.1 Pathway Interactions Appendix F
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D.2 Pathway Images Appendix Figure
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D.2 Pathway Images Appendix Figure
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E. Exon Array Data Appendix Average
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F. MicroRNA Array Data Appendix Tab
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F. MicroRNA Array Data Appendix GNS
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F. MicroRNA Array Data Appendix GNS
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Ln Natural logarithm LOH Loss of He
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3.3 Schematisation of cell cycle ph
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8.3 Workflows at the core of the pr
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7.1 Selected Gene Ontology terms an
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Bibliography [1] Cell signaling tec
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