000			03639nam a22003615i 4500
001			233384
003			ES-VaUE
005			20221220020455.0
007			cr nn 008mamaa
008			200914s2021 xxu| s |||| 0|eng d
020			_a9781071608494
024	7		_a10.1007/978-1-0716-0849-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
245	1	0	_aTranslational Bioinformatics for Therapeutic Development _cedited by Joseph Markowitz.
250			_a1st edition 2021
264		1	_aNew York, NY _bSpringer International Publising _c2021
300			_a1 recurso en línea (XV, 317 páginas) _b75 ilustraciones, 66 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 _v2194
505	0		_aDevelopment and Optimization of Clinical Informatics Infrastructure to Support Bioinformatics at an Oncology Center -- Leveraging Pathology Informatics Concepts to Achieve Discrete Lab Data for Clinical Use and Translational Research -- Cohort Identification for Translational Bioinformatics Studies -- Transitioning Clinical Practice Guidelines into the Electronic Health Record through Clinical Pathways -- Variable Selection for Time-to-Event Data -- Binary Classification for Failure Risk Assessment -- Challenges and Opportunities of Genomic Approaches in Therapeutics Development -- Accessible Pipeline for Translational Research using TCGA: Examples of Relating Gene Mechanism to Disease Specific Outcomes -- Statistical and Bioinformatics Analysis of Data from Bulk and Single-Cell RNA Sequencing Experiments -- Investigating Inter- and Intra-Sample Diversity of Single-Cell RNA Sequencing Datasets -- Managing a Large-scale Multi-Omics Project: A Team Science Case Study in Proteogenomics -- Synergistic Drug Combination Prediction by Integrating Multi-omics Data in Deep Learning Models -- Introduction to Multi-Parametric Flow Cytometry and Analysis of High-Dimensional Data -- High Dimensional Flow Cytometry Analysis of Regulatory Receptors on Human T cells, NK cells, and NKT Cells* -- Quantitative Analysis of Bile Acid with UHPLC-MS/MS -- Sample Preparation and Data Analysis for NMR-based Metabolomics. .
520			_aThis volume introduces Translational Bioinformatics as it relates to therapeutic development, and addresses the techniques needed to effectively translate large data sets to relevant biological networks. Chapters detail clinical informatics infrastructure, and leverage pathology, immunology, pharmacology, genomic, proteomic, and metabolomic informatics approaches. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, application details for both the expert and non-expert reader, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Translational Bioinformatics for Therapeutic Development: Methods and Protocols aims to ensure success in the study of Translational Bioinformatics.
700	1		_aMarkowitz, Joseph _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9781071608487
776	0	8	_iPrinted edition: _z9781071608500
776	0	8	_iPrinted edition: _z9781071608517
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-0716-0849-4 _z(usuarios Universidad Europea de Valencia)
942			_2lcc _cLE
988			_aSpringer_Protocols_2021
999			_c233384 _d233384