Probabilistic Models for Gene Silencing Data

摘要: Title Page, Preface, Contents 1\. Introduction 1.1 Signal transduction and gene regulation 1.2 Gene silencing by RNA interference 1.3 Thesis organization 2\. Statistical models of cellular networks 2.1 Conditional independence 2.2 Bayesian 2.3 Score based structure learning 2.4 Benchmarking 2.5 A roadmap to network reconstruction 3\. Inferring transcriptional regulatory 3.1 Graphical for interventional data 3.2 Ideal interventions mechanism changes 3.3 Pushing at single nodes 3.4 in conditional Gaussian networks 4\. signal pathways 4.1 Non-transcriptional modules sigaling 4.2 with phenotypes 4.3 Accuracy sample size requirements 4.4 Application Drosophila immune response 5\. Summary outlook Bibliography Zusammenfassung