Bioinformatics with Python Cookbook: Solve advanced computational biology problems and build production pipelines with Python and AI tools

Enhance your bioinformatics toolbox with practical Python recipes, tips, and tricks for key tasks like aligning sequence data, calling variants, and building Infrastructure as CodeKey FeaturesPerform sequence analysis at primary, secondary, and tertiary levels using Python librariesSolve real-world problems in the fields of phylogenetics, protein design, and annotationUse language models and other AI techniques to work with multimodal bioinformatics dataPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionIf you've ever felt overwhelmed by the vast number of Python tools available for bioinformatics, you're not alone. The Bioinformatics with Python Cookbook is a recipe-based guide that explores practical approaches for solving classic bioinformatics challenges, showing you which Python packages work best for each task.You’ll start with the essential Python libraries for data science and bioinformatics, then move through key workflows in sequencing analysis, quality control, alignment, and variant calling. Along the way, you’ll pick up modern coding practices, explore recent advances in bioinformatics research, and gain hands-on experience with libraries such as NumPy, pandas, and sci-kit learn. This book walks you through core bioinformatics tasks such as phylogenetic analysis and population genomics while familiarizing you with the wealth of modern public bioinformatics databases. You’ll learn cloud computing approaches used by researchers, set up workflow orchestration systems for controlling bioinformatics pipelines, and see how AI and the use of large language models (LLMs) are reshaping the field–right down to designing proteins and DNA.By the end of this book, you’ll be ready to apply Python for real bioinformatics work and launch bioinformatics pipelines for your research.What you will learnProcess, analyze, and align sequencing dataCall variants and interpret their biological meaningUse modern cloud infrastructure to launch bioinformatics workflowsIngest, clean, and transform data efficientlyExplore how AI is shaping the future of bioinformaticsLeverage imaging data for biological insightsApply single-cell sequencing to cluster and compare gene expressionWho this book is forThis book is for early- to mid-level practitioners in bioinformatics, data science, and software engineering who want to improve their skills and apply practical solutions to real-world problems. You should have a basic understanding of biology, including DNA, proteins, and cell structure, as well as Python programming and software engineering techniques. While prior exposure to machine learning with Python is not essential, experience with a cloud computing platform (AWS, GCP, or Azure) will be helpful.Table of ContentsComputer Specifications and Python SetupBasics of Data ManipulationModern Coding Practices and AI-Generated CodingData Science and GraphingAlignment and Variant CallingAnnotation and Biological InterpretationGenomes and Genome AssemblyAccessing Public DatabasesProtein Structure and ProteomicsPhylogeneticsPopulation GeneticsMetabolic Modeling and Other ApplicationsGenome EditingCloud BasicsWorkflow SystemsMore Workflow SystemsDeep Learning and LLMs for Nucleic Acid and Protein DesignSingle-Cell Technology and Imaging Read more