Deep Sequencing Data Analysis
Title | Deep Sequencing Data Analysis PDF eBook |
Author | Noam Shomron |
Publisher | Humana Press |
Pages | 0 |
Release | 2013-07-20 |
Genre | Science |
ISBN | 9781627035132 |
The new genetic revolution is fuelled by Deep Sequencing (or Next Generation Sequencing) apparatuses which, in essence, read billions of nucleotides per reaction. Effectively, when carefully planned, any experimental question which can be translated into reading nucleic acids can be applied.In Deep Sequencing Data Analysis, expert researchers in the field detail methods which are now commonly used to study the multi-facet deep sequencing data field. These included techniques for compressing of data generated, Chromatin Immunoprecipitation (ChIP-seq), 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 necessary materials and reagents, step-by-step, readily reproducible protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Deep Sequencing Data Analysis seeks to aid scientists in the further understanding of key data analysis procedures for deep sequencing data interpretation.
Deep Sequencing Data Analysis
Title | Deep Sequencing Data Analysis PDF eBook |
Author | Noam Shomron |
Publisher | Humana Press |
Pages | 234 |
Release | 2013-07-20 |
Genre | Science |
ISBN | 9781627035156 |
The new genetic revolution is fuelled by Deep Sequencing (or Next Generation Sequencing) apparatuses which, in essence, read billions of nucleotides per reaction. Effectively, when carefully planned, any experimental question which can be translated into reading nucleic acids can be applied.In Deep Sequencing Data Analysis, expert researchers in the field detail methods which are now commonly used to study the multi-facet deep sequencing data field. These included techniques for compressing of data generated, Chromatin Immunoprecipitation (ChIP-seq), 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 necessary materials and reagents, step-by-step, readily reproducible protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Deep Sequencing Data Analysis seeks to aid scientists in the further understanding of key data analysis procedures for deep sequencing data interpretation.
Deep Sequencing Data Analysis: Challenges and Solutions
Title | Deep Sequencing Data Analysis: Challenges and Solutions PDF eBook |
Author | Ofer Isakov |
Publisher | |
Pages | |
Release | 2011 |
Genre | |
ISBN | 9789533072821 |
Next-Generation Sequencing Data Analysis
Title | Next-Generation Sequencing Data Analysis PDF eBook |
Author | Xinkun Wang |
Publisher | CRC Press |
Pages | 252 |
Release | 2016-04-06 |
Genre | Mathematics |
ISBN | 1482217899 |
A Practical Guide to the Highly Dynamic Area of Massively Parallel SequencingThe development of genome and transcriptome sequencing technologies has led to a paradigm shift in life science research and disease diagnosis and prevention. Scientists are now able to see how human diseases and phenotypic changes are connected to DNA mutation, polymorphi
Next Generation Sequencing and Data Analysis
Title | Next Generation Sequencing and Data Analysis PDF eBook |
Author | Melanie Kappelmann-Fenzl |
Publisher | Springer Nature |
Pages | 218 |
Release | 2021-05-04 |
Genre | Science |
ISBN | 3030624900 |
This textbook provides step-by-step protocols and detailed explanations for RNA Sequencing, ChIP-Sequencing and Epigenetic Sequencing applications. The reader learns how to perform Next Generation Sequencing data analysis, how to interpret and visualize the data, and acquires knowledge on the statistical background of the used software tools. Written for biomedical scientists and medical students, this textbook enables the end user to perform and comprehend various Next Generation Sequencing applications and their analytics without prior understanding in bioinformatics or computer sciences.
Biological Sequence Analysis
Title | Biological Sequence Analysis PDF eBook |
Author | Richard Durbin |
Publisher | Cambridge University Press |
Pages | 372 |
Release | 1998-04-23 |
Genre | Science |
ISBN | 113945739X |
Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.
Bioinformatics
Title | Bioinformatics PDF eBook |
Author | Hamid D. Ismail |
Publisher | CRC Press |
Pages | 383 |
Release | 2023-06-29 |
Genre | Computers |
ISBN | 1000861708 |
This book contains the latest material in the subject, covering next generation sequencing (NGS) applications and meeting the requirements of a complete semester course. This book digs deep into analysis, providing both concept and practice to satisfy the exact need of researchers seeking to understand and use NGS data reprocessing, genome assembly, variant discovery, gene profiling, epigenetics, and metagenomics. The book does not introduce the analysis pipelines in a black box, but with detailed analysis steps to provide readers with the scientific and technical backgrounds required to enable them to conduct analysis with confidence and understanding. The book is primarily designed as a companion for researchers and graduate students using sequencing data analysis but will also serve as a textbook for teachers and students in biology and bioscience.