Genomics in the Azure Cloud: Scaling Your Bioinformatics Workloads Using Enterprise-Grade Solutions

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

這本實用指南填補了微軟Azure中一般雲計算架構與生物信息學和基因組學科學計算之間的差距。您將對Azure中提供的架構模式和服務有深入的了解，以及它們在生物信息學實踐中的應用方式。您將獲得可重複使用於特定需求的程式碼示例。並且您將獲得大量具體的示例，以說明在生物信息學背景下如何使用特定服務。

您還將獲得有價值的建議，包括：
- 使用企業平台服務輕鬆擴展生物信息學工作負載
- 組織、查詢和分析大規模基因組數據
- 構建基因組數據湖和相應的數據倉庫
- 使用Azure Machine Learning擴展模型訓練、追蹤模型性能和部署優勝模型
- 使用Azure Data Factory和Databricks編排和自動化處理流程
- 通過將工作流程移至Azure高性能計算服務，將您組織現有的生物信息學流程雲化
- 等等