Mastering Python For Bioinformatics

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Mastering Python For Bioinformatics

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Author : Ken Youens-Clark
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-05-05

Mastering Python For Bioinformatics written by Ken Youens-Clark and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-05 with Science categories.

Life scientists today urgently need training in bioinformatics skills. Too many bioinformatics programs are poorly written and barely maintained, usually by students and researchers who've never learned basic programming skills. This practical guide shows postdoc bioinformatics professionals and students how to exploit the best parts of Python to solve problems in biology while creating documented, tested, reproducible software. Ken Youens-Clark, author of Tiny Python Projects (Manning), demonstrates not only how to write effective Python code but also how to use tests to write and refactor scientific programs. You'll learn the latest Python features and tools including linters, formatters, type checkers, and tests to create documented and tested programs. You'll also tackle 14 challenges in Rosalind, a problem-solving platform for learning bioinformatics and programming. Create command-line Python programs to document and validate parameters Write tests to verify refactor programs and confirm they're correct Address bioinformatics ideas using Python data structures and modules such as Biopython Create reproducible shortcuts and workflows using makefiles Parse essential bioinformatics file formats such as FASTA and FASTQ Find patterns of text using regular expressions Use higher-order functions in Python like filter(), map(), and reduce()

Reproducible Bioinformatics With Python

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Author : Ken Youens-Clark
language : en
Publisher: O'Reilly Media
Release Date : 2021-08-17

Reproducible Bioinformatics With Python written by Ken Youens-Clark and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-17 with Computers categories.

Life scientists today urgently need training in bioinformatics skills. Too many bioinformatics programs are poorly written and barely maintained--usually by students and postdoc researchers who've never learned basic programming skills. This practical guide shows how to exploit the best parts of Python for solving problems in biology while also creating documented, tested, reproducible software. Ken Youens-Clark, author of Tiny Python Projects (Manning), demonstrates how to write effective Python code and how to use tests to write and refactor scientific programs. You'll learn the latest Python features and tools--such as linters, formatters, type checkers, and tests--to write documented and tested programs. Create command-line Python programs that document and validate parameters Write tests to verify refactor programs and confirm they're correct Address bioinformatics ideas using Python data structures (strings, lists, and sets) and modules such as Biopython Create reproducible shortcuts and workflows using makefiles Parse essential bioinformatics file formats such as FASTA, FASTQ, and SwissProt Find patterns of text using regular expressions Use higher-order functions in Python like filter() and map()

Mastering Python Data Visualization

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Author : Kirthi Raman
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-10-27

Mastering Python Data Visualization written by Kirthi Raman and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-27 with Computers categories.

Generate effective results in a variety of visually appealing charts using the plotting packages in Python About This Book Explore various tools and their strengths while building meaningful representations that can make it easier to understand data Packed with computational methods and algorithms in diverse fields of science Written in an easy-to-follow categorical style, this book discusses some niche techniques that will make your code easier to work with and reuse Who This Book Is For If you are a Python developer who performs data visualization and wants to develop existing knowledge about Python to build analytical results and produce some amazing visual display, then this book is for you. A basic knowledge level and understanding of Python libraries is assumed. What You Will Learn Gather, cleanse, access, and map data to a visual framework Recognize which visualization method is applicable and learn best practices for data visualization Get acquainted with reader-driven narratives and author-driven narratives and the principles of perception Understand why Python is an effective tool to be used for numerical computation much like MATLAB, and explore some interesting data structures that come with it Explore with various visualization choices how Python can be very useful in computation in the field of finance and statistics Get to know why Python is the second choice after Java, and is used frequently in the field of machine learning Compare Python with other visualization approaches using Julia and a JavaScript-based framework such as D3.js Discover how Python can be used in conjunction with NoSQL such as Hive to produce results efficiently in a distributed environment In Detail Python has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. Pandas have a productive environment for data analysis. These libraries have a specific purpose and play an important role in the research into diverse domains including economics, finance, biological sciences, social science, health care, and many more. The variety of tools and approaches available within Python community is stunning, and can bolster and enhance visual story experiences. This book offers practical guidance to help you on the journey to effective data visualization. Commencing with a chapter on the data framework, which explains the transformation of data into information and eventually knowledge, this book subsequently covers the complete visualization process using the most popular Python libraries with working examples. You will learn the usage of Numpy, Scipy, IPython, MatPlotLib, Pandas, Patsy, and Scikit-Learn with a focus on generating results that can be visualized in many different ways. Further chapters are aimed at not only showing advanced techniques such as interactive plotting; numerical, graphical linear, and non-linear regression; clustering and classification, but also in helping you understand the aesthetics and best practices of data visualization. The book concludes with interesting examples such as social networks, directed graph examples in real-life, data structures appropriate for these problems, and network analysis. By the end of this book, you will be able to effectively solve a broad set of data analysis problems. Style and approach The approach of this book is not step by step, but rather categorical. The categories are based on fields such as bioinformatics, statistical and machine learning, financial computation, and linear algebra. This approach is beneficial for the community in many different fields of work and also helps you learn how one approach can make sense across many fields

Immune Mediators In Cancer

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Author : Ivana Vancurova
language : en
Publisher: Springer Nature
Release Date : 2026-01-01

Immune Mediators In Cancer written by Ivana Vancurova and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-01 with Medical categories.

This second edition provides a comprehensive collection of classic and cutting-edge methodologies as well as bioinformatics and genome-editing approaches for cancer cells and tissues. Chapters beginning with the Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Immune Mediators in Cancer: Methods and Protocols, Second Edition aims to ensure successful results in the further study of this vital field.

Command Line Rust

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Author : Ken Youens-Clark
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022

Command Line Rust written by Ken Youens-Clark and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Rust (Computer program language) categories.

For several consecutive years, Rust has been voted "most loved programming language" in Stack Overflow's annual developer survey. This open source systems programming language is now used for everything from game engines and operating systems to browser components and virtual reality simulation engines. But Rust is also an incredibly complex language with a notoriously difficult learning curve. Rather than focusing on the language as a whole, this guide teaches Rust using a single small, complete, focused program in each chapter. Author Ken Youens-Clark shows you how to start, write, and test each of these programs to create a finished product. You'll learn how to handle errors in Rust, read and write files, and use regular expressions, Rust types, structs, and more. Discover how to: Use Rust's standard libraries and data types such as numbers, strings, vectors, structs, Options, and Results to create command-line programs Write and test Rust programs and functions Read and write files, including stdin, stdout, and stderr Document and validate command-line arguments Write programs that fail gracefully Parse raw and delimited text manually, using regular expressions and Rust crates Use and control randomness

Mastering Python For Finance

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Author : James Ma Weiming
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-04-30

Mastering Python For Finance written by James Ma Weiming and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-30 with Computers categories.

Take your financial skills to the next level by mastering cutting-edge mathematical and statistical financial applications Key FeaturesExplore advanced financial models used by the industry and ways of solving them using PythonBuild state-of-the-art infrastructure for modeling, visualization, trading, and moreEmpower your financial applications by applying machine learning and deep learningBook Description The second edition of Mastering Python for Finance will guide you through carrying out complex financial calculations practiced in the industry of finance by using next-generation methodologies. You will master the Python ecosystem by leveraging publicly available tools to successfully perform research studies and modeling, and learn to manage risks with the help of advanced examples. You will start by setting up your Jupyter notebook to implement the tasks throughout the book. You will learn to make efficient and powerful data-driven financial decisions using popular libraries such as TensorFlow, Keras, Numpy, SciPy, and sklearn. You will also learn how to build financial applications by mastering concepts such as stocks, options, interest rates and their derivatives, and risk analytics using computational methods. With these foundations, you will learn to apply statistical analysis to time series data, and understand how time series data is useful for implementing an event-driven backtesting system and for working with high-frequency data in building an algorithmic trading platform. Finally, you will explore machine learning and deep learning techniques that are applied in finance. By the end of this book, you will be able to apply Python to different paradigms in the financial industry and perform efficient data analysis. What you will learnSolve linear and nonlinear models representing various financial problemsPerform principal component analysis on the DOW index and its componentsAnalyze, predict, and forecast stationary and non-stationary time series processesCreate an event-driven backtesting tool and measure your strategiesBuild a high-frequency algorithmic trading platform with PythonReplicate the CBOT VIX index with SPX options for studying VIX-based strategiesPerform regression-based and classification-based machine learning tasks for predictionUse TensorFlow and Keras in deep learning neural network architectureWho this book is for If you are a financial or data analyst or a software developer in the financial industry who is interested in using advanced Python techniques for quantitative methods in finance, this is the book you need! You will also find this book useful if you want to extend the functionalities of your existing financial applications by using smart machine learning techniques. Prior experience in Python is required.

Principles Of Data Science

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Author : Sinan Ozdemir
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-12-16

Principles Of Data Science written by Sinan Ozdemir and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-16 with Computers categories.

Learn the techniques and math you need to start making sense of your data About This Book Enhance your knowledge of coding with data science theory for practical insight into data science and analysis More than just a math class, learn how to perform real-world data science tasks with R and Python Create actionable insights and transform raw data into tangible value Who This Book Is For You should be fairly well acquainted with basic algebra and should feel comfortable reading snippets of R/Python as well as pseudo code. You should have the urge to learn and apply the techniques put forth in this book on either your own data sets or those provided to you. If you have the basic math skills but want to apply them in data science or you have good programming skills but lack math, then this book is for you. What You Will Learn Get to know the five most important steps of data science Use your data intelligently and learn how to handle it with care Bridge the gap between mathematics and programming Learn about probability, calculus, and how to use statistical models to control and clean your data and drive actionable results Build and evaluate baseline machine learning models Explore the most effective metrics to determine the success of your machine learning models Create data visualizations that communicate actionable insights Read and apply machine learning concepts to your problems and make actual predictions In Detail Need to turn your skills at programming into effective data science skills? Principles of Data Science is created to help you join the dots between mathematics, programming, and business analysis. With this book, you'll feel confident about asking—and answering—complex and sophisticated questions of your data to move from abstract and raw statistics to actionable ideas. With a unique approach that bridges the gap between mathematics and computer science, this books takes you through the entire data science pipeline. Beginning with cleaning and preparing data, and effective data mining strategies and techniques, you'll move on to build a comprehensive picture of how every piece of the data science puzzle fits together. Learn the fundamentals of computational mathematics and statistics, as well as some pseudocode being used today by data scientists and analysts. You'll get to grips with machine learning, discover the statistical models that help you take control and navigate even the densest datasets, and find out how to create powerful visualizations that communicate what your data means. Style and approach This is an easy-to-understand and accessible tutorial. It is a step-by-step guide with use cases, examples, and illustrations to get you well-versed with the concepts of data science. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts later on and will help you implement these techniques in the real world.

Encyclopedia Of Genetics Genomics Proteomics And Bioinformatics 8 Volume Set

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Author : Michael J. Dunn
language : en
Publisher: Wiley
Release Date : 2005-11-11

Encyclopedia Of Genetics Genomics Proteomics And Bioinformatics 8 Volume Set written by Michael J. Dunn and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-11-11 with Science categories.

Available in print and online, this unique reference brings together all four fields of genetics, genomics, proteomics, and bioinformatics to meet your dynamic research requirements. It brings together the latest concepts in these vibrant areas and ensures a truly multidisciplinary approach. Topics include genetic variation and evolution, epigenetics, the human genome, expression profiling, proteome families, structural proteomics, gene finding/gene structure, protein function and annotation, and more. The work incorporates a vast amount of topical information, profiles cutting-edge techniques, and presents the very latest findings from an international team of over five hundred contributors. With articles for both students and more experienced scientists, this is a key reference source for everyone. Contains more than 450 articles covering all aspects of genomics, proteomics, bioinformatics and related technologies Includes a glossary containing over 550 clear and concise definitions "I am pleased to recommend it heartily as a essential reference tool...should remain the definitive work...for many years to come." THE CHEMICAL EDUCATOR "Jorde...and co-editors have done a remarkable job in coordinating this information, distilling it into a package that is both easy to navigate and over-flowing in discovery." ELECTRIC REVIEW

Bioinformatics Programming Using Python

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Author : Mitchell L Model
language : en
Publisher:
Release Date : 2010

Bioinformatics Programming Using Python written by Mitchell L Model and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.

Python Fast Track

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Author : Sanjiban Sekhar Roy
language : en
Publisher: Elsevier
Release Date : 2025-06-30

Python Fast Track written by Sanjiban Sekhar Roy and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-30 with Computers categories.

Python Fast Track: A Complete Guide to Rapidly Mastering and Applying Python Programming adopts a simplified writing style and provides clear explanations to ensure ease of understanding, making it an ideal resource for those new to Python. Starting with the basics, the book covers fundamental concepts such as variables, data types, printing and prompting, lists, dictionaries, tuples, control structure, functions, and object-oriented concepts. The book includes everything you need to understand and apply more advanced programming techniques such as file handling, exception handling, and regex.This great resource is created especially for those who want to apply Python for their research and professional work in scientific computing, data analysis and machine learning, including chapters on NumPy and Pandas, two of the most popular Python application libraries. It demonstrates how to effectively master key applications of Python such as web development, software creation, task automation, and data analysis. The book covers data analysis and machine learning tasks that greatly benefit from Python, thanks to libraries such as TensorFlow and Keras that enable efficient coding. - Explains the core concepts of Python programming in a simplified way that is suitable for people who have little or no programming experience - Incorporates a wide range of simple, step-by-step examples and illustrations to highlight fundamental concepts so readers can learn easily - Provides practice exercises designed to expedite the learning process and provide hands-on application experience - Offers a wide range of functionality, from basic processes to complex operations, including chapters on Pandas and NumPy, two of the most popular Python libraries for data analysis