Overview

This practical guide bridges the gap between general cloud computing architecture in Microsoft Azure and scientific computing for bioinformatics and genomics. You'll get a solid understanding of the architecture patterns and services that are offered in Azure and how they might be used in your bioinformatics practice. You'll get code examples that you can reuse for your specific needs. And you'll get plenty of concrete examples to illustrate how a given service is used in a bioinformatics context. You'll also get valuable advice on how to: Use enterprise platform services to easily scale your bioinformatics workloads Organize, query, and analyze genomic data at scale Build a genomics data lake and accompanying data warehouse Use Azure Machine Learning to scale your model training, track model performance, and deploy winning models Orchestrate and automate processing pipelines using Azure Data Factory and Databricks Cloudify your organization's existing bioinformatics pipelines by moving your workflows to Azure high-performance compute services And more

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9781098139049

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Dr. Colby T. Ford is a professional AI cloud architect, data scientist, and computational biologist who uses machine learning and distributed computing to solve problems in the fields of infectious diseases and human genomics. For the last 8+ years, he has been consulting for companies across industries, leading the conversation for digital transformation using artificial intelligence and cloud computing. He currently serves as the Principal of Life Sciences at BlueGranite, a top-tier Microsoft partner, and focuses on building cloud-based bioinformatics solutions in the Azure cloud. In academia, his research includes the use of large-scale machine learning architecture in the study of infectious disease genomics and rare human diseases. In addition to his consulting and academic career, Dr. Ford is a co-founder of a digital health startup that focuses on the use of wearable devices to help study neurological disorders. Given Dr. Ford's interdisciplinary education background and parallel experience in industry and academia, he has a unique viewpoint and approach to effectively solve genomics research problems with cutting-edge technologies previously only used in industry blended with methods previously only seen in academia.

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