Bioinformatics with Python Cookbook, 3/e (Paperback)

Discover modern, next-generation sequencing libraries from the powerful Python ecosystem to perform cutting-edge research and analyze large amounts of biological data

Key Features:

• Perform complex bioinformatics analysis using the most essential Python libraries and applications
• Implement next-generation sequencing, metagenomics, automating analysis, population genetics, and much more
• Explore various statistical and machine learning techniques for bioinformatics data analysis

Book Description:

Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data, and this book will show you how to manage these tasks using Python.

This updated third edition of the Bioinformatics with Python Cookbook begins with a quick overview of the various tools and libraries in the Python ecosystem that will help you convert, analyze, and visualize biological datasets. Next, you'll cover key techniques for next-generation sequencing, single-cell analysis, genomics, metagenomics, population genetics, phylogenetics, and proteomics with the help of real-world examples. You'll learn how to work with important pipeline systems, such as Galaxy servers and Snakemake, and understand the various modules in Python for functional and asynchronous programming. This book will also help you explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks, including Dask and Spark. In addition to this, you'll explore the application of machine learning algorithms in bioinformatics.

By the end of this bioinformatics Python book, you'll be equipped with the knowledge you need to implement the latest programming techniques and frameworks, empowering you to deal with bioinformatics data on every scale.

What You Will Learn:

• Become well-versed with data processing libraries such as NumPy, pandas, arrow, and zarr in the context of bioinformatic analysis
• Interact with genomic databases
• Solve real-world problems in the fields of population genetics, phylogenetics, and proteomics
• Build bioinformatics pipelines using a Galaxy server and Snakemake
• Work with functools and itertools for functional programming
• Perform parallel processing with Dask on biological data
• Explore principal component analysis (PCA) techniques with scikit-learn

Who this book is for:

This book is for bioinformatics analysts, data scientists, computational biologists, researchers, and Python developers who want to address intermediate-to-advanced biological and bioinformatics problems. Working knowledge of the Python programming language is expected. Basic knowledge of biology will also be helpful.

發現現代、下一代的Python強大生態系統中的序列分析函式庫，以進行尖端研究和分析大量生物資料。

主要特點：
- 使用最重要的Python函式庫和應用程式進行複雜的生物資訊分析。
- 實施下一代的序列分析、宏基因組學、自動化分析、群體遺傳學等。
- 探索各種統計和機器學習技術，進行生物資訊資料分析。

書籍描述：
生物資訊是一個活躍的研究領域，利用一系列從生物資料中提取有價值資訊的簡單到高級的計算方法。本書將向您展示如何使用Python來處理這些任務。

本書的第三版更新版首先快速概述了Python生態系統中的各種工具和函式庫，這些工具和函式庫將幫助您轉換、分析和視覺化生物資料集。接下來，您將通過實際示例學習下一代序列分析、單細胞分析、基因組學、宏基因組學、群體遺傳學、親緣關係學和蛋白質組學的關鍵技術。您將學習如何使用重要的流程系統，例如Galaxy伺服器和Snakemake，並了解Python中用於功能和非同步編程的各種模塊。本書還將幫助您探索在高性能計算框架（包括Dask和Spark）下使用統計方法進行SNP發現。此外，您還將探索在生物資訊中應用機器學習算法。

通過閱讀本生物資訊Python書籍，您將掌握實施最新的編程技術和框架所需的知識，使您能夠處理各種規模的生物資訊資料。

您將學到什麼：
- 熟悉NumPy、pandas、arrow和zarr等資料處理函式庫，並將其應用於生物資訊分析。
- 與基因組資料庫互動。
- 解決人口遺傳學、親緣關係學和蛋白質組學等領域的實際問題。
- 使用Galaxy伺服器和Snakemake構建生物資訊流程。
- 使用functools和itertools進行功能編程。
- 使用Dask在生物資料上進行並行處理。
- 使用scikit-learn探索主成分分析（PCA）技術。

本書適合對生物資訊分析、資料科學家、計算生物學家、研究人員和Python開發人員，他們希望解決中高級生物和生物資訊問題。預期讀者具備Python編程語言的工作知識，基本的生物學知識也將有所幫助。