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008			210219s2021 xxu| o |||| 0|eng d
020			_a9781071611036
024	7		_a10.1007/978-1-0716-1103-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQP625 .N89 _b2021 EB
245	0	0	_aDeep Sequencing Data Analysis _cedited by Noam Shomron
250			_a2nd edition 2021
264		1	_aNew York, NY _bSpringer International Publising _c2021
300			_a1 recurso en línea (X, 374 páginas) _b92 ilustraciones, 81 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 _v2243
505	0		_aDetecting Causal Variants in Mendelian Disorders using Whole Genome Sequencing -- Statistical Considerations on NGS Data for Inferring Copy Number Variations -- Applications of Community Detection Algorithms to Large Biological Datasets -- Processing and Analysis of RNA-seq data from Public Resources -- Improved Analysis of High-throughput Sequencing Data Using Small Universal k-mer Hitting Sets -- An Introduction to Whole-metagenome Shotgun Sequencing Studies -- Microbiome Analysis using 16S Amplicon Sequencing: From Samples to ASVs -- RNA-Seq in Non-model Organisms -- Deep Learning Applied on Next Generation Sequencing Data Analysis -- Interrogating the Accessible Chromatin Landscape of Eukaryote Genomes using ATAC-seq -- Genome-Wide Noninvasive Prenatal Diagnosis of SNPs and Indels -- Genome-wide Noninvasive Prenatal Diagnosis of De Novo Mutations -- Accurate Imputation of Untyped Variants from Deep Sequencing Data -- Multi-region Sequence Analysis to Predict Intratumor Heterogeneity and Clonal Evolution -- Overcoming Interpretability in Deep Learning Cancer Classification -- Single-cell Transcriptome Profiling -- Biological Perspectives of RNA-sequencing Experimental Design -- Analysis of microRNA Regulation in Single Cells -- DNA Data Collection and Analysis in the Forensic Arena. .
520			_aThis second edition provides new and updated chapters from expert researchers in the field detailing methods used to study the multi-facet deep sequencing data field. Chapters guide readers through techniques for processing RNA-seq data, microbiome analysis, deep learning methodologies, and various approaches for the identification of sequence variants. 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 cutting-edge, Deep Sequencing Data Analysis: Methods and Protocols, Second Edition aims to ensure successful results in the further study of this vital field.
988			_aSpringer_Protocols_2021
650		7	_2embne _9144345 _aNucleótidos _vManuales de laboratorio
776	0	8	_iPrinted edition: _z9781071611029
776	0	8	_iPrinted edition: _z9781071611043
776	0	8	_iPrinted edition: _z9781071611050
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-0716-1103-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b08/2023 _dz _eu _zSI