Buch, Englisch, Band 1711, 402 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 1294 g
Reihe: Methods in Molecular Biology
Methods and Protocols
Buch, Englisch, Band 1711, 402 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 1294 g
Reihe: Methods in Molecular Biology
ISBN: 978-1-4939-7492-4
Verlag: Springer
This book comprises protocols describing systems biology methodologies and computational tools, offering a variety of ways to analyze different types of high-throughput cancer data. Chapters give an overview over data types available in large-scale data repositories and state-of-the-art methods used in the field of cancer systems biology. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.
Authoritative and practical, Cancer Systems Biology : Methods and Protocols aims to ensure successful results in the further study of this vital field.
The chapters "Identifying Genetic Dependencies in Cancer by Analyzing siRNA Screens in Tumor Cell Line Panels", "Perseus: A Bioinformatics Platform for Integrative Analysisof Proteomics Data in Cancer Research" and "Phosphoproteomics-based Profiling of Kinase Activities in Cancer Cells" are available open access under a CC BY 4.0 license via link.springer.com.
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Weitere Infos & Material
Detection of Combinatorial Mutational Patterns in Human Cancer Genomes by Exclusivity Analysis.- Discovering Altered Regulation and Signaling Through Network-based Integration of Transcriptomic, Epigenomic, and Proteomic Tumor Data.- Analyzing DNA Methylation Patterns during Tumor Evolution.- MicroRNA Networks in Breast Cancer Cells.- Identifying Genetic Dependencies in Cancer by Analyzing siRNA Screens in Tumor Cell Line Panels.- Phosphoproteomics-based Profiling of Kinase Activities in Cancer Cells.- Perseus: A Bioinformatics Platform for Integrative Analysis of Proteomics Data in Cancer Research.- Quantitative Analysis of Tyrosine Kinase Signaling Across Differentially Embedded Human Glioblastoma Tumors.- Prediction of Clinical Endpoints in Breast Cancer using NMR Metabolic Profiles.- Stochastic and Deterministic Models for the Metastatic Emission Process: Formalisms and Crosslinks.- Mechanically Coupled Reaction-Diffusion Model to Predict Glioma Growth: Methodological Details.- Profiling Tumor Infiltrating Immune Cells with CIBERSORT.- Systems Biology Approaches in Cancer Pathology.- Bioinformatics Approaches to Predict Drug Responses from Genomic Sequencing.- A Robust Optimization Approach to Cancer Treatment under Toxicity Uncertainty.- Modeling of Interactions between Cancer Stem Cells and their Microenvironment: Predicting Clinical Response.- Methods for High-throughput Drug Combination Screening and Synergy Scoring.
