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Genomics In The Cloud

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Genomics In The Cloud

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Author : Geraldine A. Van der Auwera
language : en
Publisher: O'Reilly Media
Release Date : 2020-04-02

Genomics In The Cloud written by Geraldine A. Van der Auwera and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-02 with Science categories.

Data in the genomics field is booming. In just a few years, organizations such as the National Institutes of Health (NIH) will host 50+ petabytesâ??or over 50 million gigabytesâ??of genomic data, and theyâ??re turning to cloud infrastructure to make that data available to the research community. How do you adapt analysis tools and protocols to access and analyze that volume of data in the cloud? With this practical book, researchers will learn how to work with genomics algorithms using open source tools including the Genome Analysis Toolkit (GATK), Docker, WDL, and Terra. Geraldine Van der Auwera, longtime custodian of the GATK user community, and Brian Oâ??Connor of the UC Santa Cruz Genomics Institute, guide you through the process. Youâ??ll learn by working with real data and genomics algorithms from the field. This book covers: Essential genomics and computing technology background Basic cloud computing operations Getting started with GATK, plus three major GATK Best Practices pipelines Automating analysis with scripted workflows using WDL and Cromwell Scaling up workflow execution in the cloud, including parallelization and cost optimization Interactive analysis in the cloud using Jupyter notebooks Secure collaboration and computational reproducibility using Terra

Genomics In The Cloud

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Author : Geraldine Van der Auwera
language : en
Publisher:
Release Date : 2020

Genomics In The Cloud written by Geraldine Van der Auwera and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.

Data in the genomics field is booming. In just a few years, organizations such as the National Institutes of Health (NIH) will host 50+ petabytes-or 52.4 million gigabytes-of genomic data, and they're turning to cloud infrastructure to make that data available to the research community. How do you adapt analysis tools and protocols to access and analyze that data in the cloud? With this practical book, researchers will learn how to work with genomics algorithms using open source tools including the Genome Analysis Toolkit (GATK), Docker, WDL, and Terra. Brian O'Connor of the UC Santa Cruz Genomics Institute and Geraldine Van der Auwera, longtime custodian of the GATK user community, guide you through the process. You'll learn by working with real data and genomics algorithms from the field. This book takes you through: Essential genomics and computing technology background Basic cloud computing operations Getting started with GATK Three major GATK best practices for variant discovery pipelines Automating analysis with scripted workflows using WDL and Cromwell Scaling up workflow execution in the cloud, including parallelization and cost optimization Interactive analysis in the cloud using Jupyter notebooks Secure collaboration and computational reproducibility using Terra.

Genomics In The Cloud

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Author : Geraldine A. Van der Auwera
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2020-04-02

Genomics In The Cloud written by Geraldine A. Van der Auwera and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-02 with Science categories.

Biotechnology Concepts Methodologies Tools And Applications

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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2019-06-07

Biotechnology Concepts Methodologies Tools And Applications written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-07 with Science categories.

Biotechnology can be defined as the manipulation of biological process, systems, and organisms in the production of various products. With applications in a number of fields such as biomedical, chemical, mechanical, and civil engineering, research on the development of biologically inspired materials is essential to further advancement. Biotechnology: Concepts, Methodologies, Tools, and Applications is a vital reference source for the latest research findings on the application of biotechnology in medicine, engineering, agriculture, food production, and other areas. It also examines the economic impacts of biotechnology use. Highlighting a range of topics such as pharmacogenomics, biomedical engineering, and bioinformatics, this multi-volume book is ideally designed for engineers, pharmacists, medical professionals, practitioners, academicians, and researchers interested in the applications of biotechnology.

Genomics In The Aws Cloud

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Author : Catherine Vacher
language : en
Publisher: John Wiley & Sons
Release Date : 2023-04-19

Genomics In The Aws Cloud written by Catherine Vacher and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-19 with Science categories.

Perform genome analysis and sequencing of data with Amazon Web Services Genomics in the AWS Cloud: Analyzing Genetic Code Using Amazon Web Services enables a person who has moderate familiarity with AWS Cloud to perform full genome analysis and research. Using the information in this book, you'll be able to take a FASTQ file containing raw data from a lab or a BAM file from a service provider and perform genome analysis on it. You'll also be able to identify potentially pathogenic gene sequences. Get an introduction to Whole Genome Sequencing (WGS) Make sense of WGS on AWS Master AWS services for genome analysis Some key advantages of using AWS for genomic analysis is to help researchers utilize a wide choice of compute services that can process diverse datasets in analysis pipelines. Genomic sequencers that generate raw data files are located in labs on premises and AWS provides solutions to make it easy for customers to transfer these files to AWS reliably and securely. Storing Genomics and Medical (e.g., imaging) data at different stages requires enormous storage in a cost-effective manner. Amazon Simple Storage Service (Amazon S3), Amazon Glacier, and Amazon Elastics Block Store (Amazon EBS) provide the necessary solutions to securely store, manage, and scale genomic file storage. Moreover, the storage services can interface with various compute services from AWS to process these files. Whether you're just getting started or have already been analyzing genomics data using the AWS Cloud, this book provides you with the information you need in order to use AWS services and features in the ways that will make the most sense for your genomic research.

Bioinformatics And Human Genomics Research

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Author : Diego A. Forero
language : en
Publisher: CRC Press
Release Date : 2021-12-23

Bioinformatics And Human Genomics Research written by Diego A. Forero and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-23 with Science categories.

Advances in high-throughput biological methods have led to the publication of a large number of genome-wide studies in human and animal models. In this context, recent tools from bioinformatics and computational biology have been fundamental for the analysis of these genomic studies. The book Bioinformatics and Human Genomics Research provides updated and comprehensive information about multiple approaches of the application of bioinformatic tools to research in human genomics. It covers strategies analysis of genome-wide association studies, genome-wide expression studies and genome-wide DNA methylation, among other topics. It provides interesting strategies for data mining in human genomics, network analysis, prediction of binding sites for miRNAs and transcription factors, among other themes. Experts from all around the world in bioinformatics and human genomics have contributed chapters in this book. Readers will find this book as quite useful for their in silico explorations, which would contribute to a better and deeper understanding of multiple biological processes and of pathophysiology of many human diseases.

Introduction To Genomics

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Author : Arthur M. Lesk
language : en
Publisher: Oxford University Press
Release Date : 2017

Introduction To Genomics written by Arthur M. Lesk and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Science categories.

The most up-to-date and complete textbook for first time genomics students, Introduction to Genomics offers a fascinating insight into how organisms differ or match; how different organisms evolved; how the genome is constructed and how it operates; and what our understanding of genomics means in terms of our future health and wellbeing. -This fully updated and restructured new edition, which includes two new chapters, takes account of new developments and technologies, presenting a logical and coherent overview of genome science today. -The author's widely-praised writing style leads the reader through a conceptually challenging subject in a clear, lucid way, building confidence in, and enthusiasm for, the subject at the outset. -Broad and fascinating range of 'real world' examples, which are also relevant across genet.

Genomics Of Pathogens And Vectors

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Author : Tulio de Lima Campos
language : en
Publisher: Frontiers Media SA
Release Date : 2024-09-27

Genomics Of Pathogens And Vectors written by Tulio de Lima Campos and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-27 with Science categories.

We are delighted to announce a thematic issue focused on the molecular epidemiology of pathogens and vectors of disease. In the last decades, genomics has revolutionized many areas of science, technology, and health by enlightening our understanding of the intricate molecular biology of pathogens and vectors. Despite these advances viral, bacterial, fungal, and parasitic pathogens still cause huge economic and health losses around the world. Moreover, there is compelling evidence of an expansion of their impact linked to global warming, anthropogenic activities and/or limitations in control strategies. Vectored pathogens are also highly relevant, causing diseases with severe morbidity and mortality such as malaria, dengue fever and schistosomiasis. The expanding geographical reach of vectors due to adaptation and/or climate change is leading to outbreaks in previously unaffected areas. Substantial challenges remain to track and trace pathogens and vectors through molecular signatures in order to understand their impact to human and animal health in different environments.

Deep Learning For Genomics

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Author : Upendra Kumar Devisetty
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-11-11

Deep Learning For Genomics written by Upendra Kumar Devisetty and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-11 with Computers categories.

Learn concepts, methodologies, and applications of deep learning for building predictive models from complex genomics data sets to overcome challenges in the life sciences and biotechnology industries Key FeaturesApply deep learning algorithms to solve real-world problems in the field of genomicsExtract biological insights from deep learning models built from genomic datasetsTrain, tune, evaluate, deploy, and monitor deep learning models for enabling predictions in genomicsBook Description Deep learning has shown remarkable promise in the field of genomics; however, there is a lack of a skilled deep learning workforce in this discipline. This book will help researchers and data scientists to stand out from the rest of the crowd and solve real-world problems in genomics by developing the necessary skill set. Starting with an introduction to the essential concepts, this book highlights the power of deep learning in handling big data in genomics. First, you'll learn about conventional genomics analysis, then transition to state-of-the-art machine learning-based genomics applications, and finally dive into deep learning approaches for genomics. The book covers all of the important deep learning algorithms commonly used by the research community and goes into the details of what they are, how they work, and their practical applications in genomics. The book dedicates an entire section to operationalizing deep learning models, which will provide the necessary hands-on tutorials for researchers and any deep learning practitioners to build, tune, interpret, deploy, evaluate, and monitor deep learning models from genomics big data sets. By the end of this book, you'll have learned about the challenges, best practices, and pitfalls of deep learning for genomics. What you will learnDiscover the machine learning applications for genomicsExplore deep learning concepts and methodologies for genomics applicationsUnderstand supervised deep learning algorithms for genomics applicationsGet to grips with unsupervised deep learning with autoencodersImprove deep learning models using generative modelsOperationalize deep learning models from genomics datasetsVisualize and interpret deep learning modelsUnderstand deep learning challenges, pitfalls, and best practicesWho this book is for This deep learning book is for machine learning engineers, data scientists, and academicians practicing in the field of genomics. It assumes that readers have intermediate Python programming knowledge, basic knowledge of Python libraries such as NumPy and Pandas to manipulate and parse data, Matplotlib, and Seaborn for visualizing data, along with a base in genomics and genomic analysis concepts.

Deep Learning In Genetics And Genomics

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Author : Khalid Raza
language : en
Publisher: Elsevier
Release Date : 2024-11-28

Deep Learning In Genetics And Genomics written by Khalid Raza and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-28 with Science categories.

Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications, the intersection of deep learning and genetics opens up new avenues for advancing our understanding of the genetic code, gene regulation, and the broader genomics landscape. The book not only covers the most up-to-date advancements in the field of deep learning in genetics and genomics, but also a wide spectrum of (sub) topics including medical and clinical genetics, predictive medicine, transcriptomic, and gene expression studies. In 21 chapters Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications describes how AI and DL have become increasingly useful in genetics and genomics research where both play a crucial role by accelerating research, improving the understanding of the human genome, and enabling personalized healthcare. From the fundamentals concepts and practical applications of deep learning algorithms to a wide range of challenging problems from genetics and genomics, Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications creates a better knowledge of the biological and genetics mechanisms behind disease illnesses and improves the forecasting abilities using the different methodologies described. This title offers a unique resource for wider, deeper, and in-depth coverage of recent advancement in deep learning-based approaches in genetics and genomics, helping researchers process and interpret vast amounts of genetic data, identify patterns, and make discoveries that would be challenging or impossible using traditional methods. - Brings together fundamental concepts of genetics, genomics, and deep learning - Includes how to build background of solution methodologies and design of mathematical and logical algorithms - Delves into the intersection of deep learning and genetics, offering a comprehensive exploration of how deep learning techniques can be applied to various aspects of genomics

Genomics In The Cloud

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