Tiago Antao's Books

Bioinformatics with Python Cookbook

By: Tiago Antao

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Bioinformatics with Python Cookbook

By: Tiago Antao

If you are either a computational biologist or a Python programmer, you will probably relate to the expression "explosive growth, exciting times". Python is arguably the main programming language for big data, and the deluge of data in biology, mostly from genomics and proteomics, makes bioinformatics one of the most exciting fields in data science. Using the hands-on recipes in this book, you'll be able to do practical research and analysis in computational biology with Python. We cover modern, next-generation sequencing libraries and explore real-world examples on how to handle real data. The main focus of the book is the practical application of bioinformatics, but we also cover modern programming techniques and frameworks to deal with the ever increasing deluge of bioinformatics data.

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306

Publisher

Packt Publishing Ltd

Published Date

ISBN 10

1783558652

ISBN 13

9781783558650

Fast Python

High performance techniques for large datasets

By: Tiago Antao

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Fast Python

High performance techniques for large datasets

By: Tiago Antao

Master Python techniques and libraries to reduce run times, efficiently handle huge datasets, and optimize execution for complex machine learning applications. Fast Python is a toolbox of techniques for high performance Python including: Writing efficient pure-Python code Optimizing the NumPy and pandas libraries Rewriting critical code in Cython Designing persistent data structures Tailoring code for different architectures Implementing Python GPU computing Fast Python is your guide to optimizing every part of your Python-based data analysis process, from the pure Python code you write to managing the resources of modern hardware and GPUs. You'll learn to rewrite inefficient data structures, improve underperforming code with multithreading, and simplify your datasets without sacrificing accuracy. Written for experienced practitioners, this book dives right into practical solutions for improving computation and storage efficiency. You'll experiment with fun and interesting examples such as rewriting games in Cython and implementing a MapReduce framework from scratch. Finally, you'll go deep into Python GPU computing and learn how modern hardware has rehabilitated some former antipatterns and made counterintuitive ideas the most efficient way of working. About the Technology Face it. Slow code will kill a big data project. Fast pure-Python code, optimized libraries, and fully utilized multiprocessor hardware are the price of entry for machine learning and large-scale data analysis. What you need are reliable solutions that respond faster to computing requirements while using less resources, and saving money. About the Book Fast Python is a toolbox of techniques for speeding up Python, with an emphasis on big data applications. Following the clear examples and precisely articulated details, you’ll learn how to use common libraries like NumPy and pandas in more performant ways and transform data for efficient storage and I/O. More importantly, Fast Python takes a holistic approach to performance, so you’ll see how to optimize the whole system, from code to architecture. What’s Inside Rewriting critical code in Cython Designing persistent data structures Tailoring code for different architectures Implementing Python GPU computing About the Reader For intermediate Python programmers familiar with the basics of concurrency. About the Author Tiago Antão is one of the co-authors of Biopython, a major bioinformatics package written in Python. Table of Contents: PART 1 - FOUNDATIONAL APPROACHES 1 An urgent need for efficiency in data processing 2 Extracting maximum performance from built-in features 3 Concurrency, parallelism, and asynchronous processing 4 High-performance NumPy PART 2 - HARDWARE 5 Re-implementing critical code with Cython 6 Memory hierarchy, storage, and networking PART 3 - APPLICATIONS AND LIBRARIES FOR MODERN DATA PROCESSING 7 High-performance pandas and Apache Arrow 8 Storing big data PART 4 - ADVANCED TOPICS 9 Data analysis using GPU computing 10 Analyzing big data with Dask

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302

Publisher

Simon and Schuster

Published Date

ISBN 10

1638356866

ISBN 13

9781638356868

Inventing a European Nation

Engineers for Portugal, from Baroque to Fascism

By: Maria Paula Diogo,Tiago Saraiva

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Inventing a European Nation

Engineers for Portugal, from Baroque to Fascism

By: Maria Paula Diogo,Tiago Saraiva

This book deals with the simultaneous making of Portuguese engineers and the Portuguese nation-state from the mid seventeenth century to the late twentieth century. It argues that the different meanings of being an engineer were directly dependent of projects of nation building and that one cannot understand the history of engineering in Portugal without detailing such projects. Symmetrically, the authors suggest that the very same ability of collectively imagining a nation relied on large measure on engineers and their practices. National culture was not only enacted through poetry, music, and history, but it demanded as well fortresses, railroads, steam engines, and dams. Portuguese engineers imagined their country in dialogue with Italian, British, French, German or American realities, many times overlapping such references. The book exemplifies how history of engineering makes more salient the transnational dimensions of national history. This is valid beyond the Portuguese case and draws attention to the potential of history of engineering for reshaping national histories and their local specificities into global narratives relevant for readers across different geographies.

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Page Count

151

Publisher

Springer Nature

Published Date

ISBN 10

3031021290

ISBN 13

9783031021299

Bioinformatics with Python Cookbook

Use modern Python libraries and applications to solve real-world computational biology problems

By: Tiago Antao

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Bioinformatics with Python Cookbook

Use modern Python libraries and applications to solve real-world computational biology problems

By: Tiago Antao

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.

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Page Count

360

Publisher

Packt Publishing Ltd

Published Date

ISBN 10

180324772X

ISBN 13

9781803247724

Fast Python

High Performance Techniques for Large Datasets

By: Tiago Antao

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Fast Python

High Performance Techniques for Large Datasets

By: Tiago Antao

Master these effective techniques to reduce costs and run times, handle huge datasets, and implement complex machine learning applications efficiently in Python. Fast Python is a hands-on guide to writing Python code that can process more data, faster, and with less resources. It takes a holistic approach to Python performance, showing you how your code, libraries, and computing architecture interact and can be optimized together. Written for experienced practitioners, Fast Python dives right into practical solutions for improving computation and storage efficiency. You'll experiment with fun and interesting examples such as rewriting games in lower-level Cython and implementing a MapReduce framework from scratch. Finally, you'll go deep into Python GPU computing and learn how modern hardware has rehabilitated some former antipatterns and made counterintuitive ideas the most efficient way of working. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

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302

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Simon and Schuster

Published Date

ISBN 10

1617297933

ISBN 13

9781617297939

Bioinformatics with Python Cookbook

Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology

By: Tiago Antao

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Bioinformatics with Python Cookbook

Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology

By: Tiago Antao

Discover modern, next-generation sequencing libraries from Python ecosystem to analyze large amounts of biological data Key Features Perform complex bioinformatics analysis using the most important Python libraries and applications Implement next-generation sequencing, metagenomics, automating analysis, population genetics, and 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. This book covers next-generation sequencing, genomics, metagenomics, population genetics, phylogenetics, and proteomics. You'll learn modern programming techniques to analyze large amounts of biological data. With the help of real-world examples, you'll convert, analyze, and visualize datasets using various Python tools and libraries. This book will help you get a better understanding of working with a Galaxy server, which is the most widely used bioinformatics web-based pipeline system. This updated edition also includes advanced next-generation sequencing filtering techniques. You'll also explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks such as Dask and Spark. By the end of this book, you'll be able to use and implement modern programming techniques and frameworks to deal with the ever-increasing deluge of bioinformatics data. What you will learn Learn how to process large next-generation sequencing (NGS) datasets Work with genomic dataset using the FASTQ, BAM, and VCF formats Learn to perform sequence comparison and phylogenetic reconstruction Perform complex analysis with protemics data Use Python to interact with Galaxy servers Use High-performance computing techniques with Dask and Spark Visualize protein dataset interactions using Cytoscape Use PCA and Decision Trees, two machine learning techniques, with biological datasets Who this book is for This book is for Data data Scientistsscientists, Bioinformatics bioinformatics analysts, researchers, and Python developers who want to address intermediate-to-advanced biological and bioinformatics problems using a recipe-based approach. Working knowledge of the Python programming language is expected.

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352

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Packt Publishing Ltd

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ISBN 10

1789349982

ISBN 13

9781789349986

Book's by Tiago Antao

Bioinformatics with Python Cookbook

Bioinformatics with Python Cookbook

Fast Python

Fast Python

Inventing a European Nation

Inventing a European Nation

Bioinformatics with Python Cookbook

Bioinformatics with Python Cookbook

Fast Python

Fast Python

Bioinformatics with Python Cookbook

Bioinformatics with Python Cookbook

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