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008			180117s2018 xxua o |||| 0|eng d
020			_a9781493974931
024	7		_a10.1007/978-1-4939-7493-1 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aRC269.7 _b2018 EB
245	0	0	_aCancer Systems Biology : _bMethods and Protocols _cedited by Louise von Stechow
250			_a1st edition 2018
264		1	_aNew York, NY _bSpringer International Publishing _c2018
300			_a1 recurso en línea (XI, 402 páginas) _b86 ilustraciones, 76 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aMethods in Molecular Biology _x1940-6029 _v1711
505	0		_aDetection 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. .
520			_aThis 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 Analysis of 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.
988			_aSpringer_Protocols_2018
650		7	_2embne _9146156 _aCélulas cancerosas
776	0	8	_iPrinted edition: _z9781493974924
776	0	8	_iPrinted edition: _z9781493974948
776	0	8	_iPrinted edition: _z9781493985036
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-4939-7493-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b07/2023 _dz _eb _zSI