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Bioinformatics Data Skills

Author: Vince Buffalo
Publisher: "O'Reilly Media, Inc."
ISBN: 144936750X
Size: 75.62 MB
Format: PDF, Mobi
View: 3647
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Learn the data skills necessary for turning large sequencing datasets into reproducible and robust biological findings. With this practical guide, you’ll learn how to use freely available open source tools to extract meaning from large complex biological data sets. At no other point in human history has our ability to understand life’s complexities been so dependent on our skills to work with and analyze data. This intermediate-level book teaches the general computational and data skills you need to analyze biological data. If you have experience with a scripting language like Python, you’re ready to get started. Go from handling small problems with messy scripts to tackling large problems with clever methods and tools Process bioinformatics data with powerful Unix pipelines and data tools Learn how to use exploratory data analysis techniques in the R language Use efficient methods to work with genomic range data and range operations Work with common genomics data file formats like FASTA, FASTQ, SAM, and BAM Manage your bioinformatics project with the Git version control system Tackle tedious data processing tasks with with Bash scripts and Makefiles

Bioinformatics Data Skills

Author: Vince Buffalo
Publisher: "O'Reilly Media, Inc."
ISBN: 1449367518
Size: 80.22 MB
Format: PDF
View: 6271
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Learn the data skills necessary for turning large sequencing datasets into reproducible and robust biological findings. With this practical guide, you’ll learn how to use freely available open source tools to extract meaning from large complex biological data sets. At no other point in human history has our ability to understand life’s complexities been so dependent on our skills to work with and analyze data. This intermediate-level book teaches the general computational and data skills you need to analyze biological data. If you have experience with a scripting language like Python, you’re ready to get started. Go from handling small problems with messy scripts to tackling large problems with clever methods and tools Process bioinformatics data with powerful Unix pipelines and data tools Learn how to use exploratory data analysis techniques in the R language Use efficient methods to work with genomic range data and range operations Work with common genomics data file formats like FASTA, FASTQ, SAM, and BAM Manage your bioinformatics project with the Git version control system Tackle tedious data processing tasks with with Bash scripts and Makefiles

Bioinformatics Data Skills

Author: Vince Buffalo
Publisher: O'Reilly Media
ISBN: 9781449367374
Size: 25.61 MB
Format: PDF, Docs
View: 5234
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This practical book teaches the skills that scientists need for turning large sequencing datasets into reproducible and robust biological findings. Many biologists begin their bioinformatics training by learning languages like Perl and R alongside the Unix command line. But there's a huge gap between knowing a few programming languages and being prepared to analyze large amounts of biological data. Rather than teach bioinformatics as a set of workflows that are likely to change with this rapidly evolving field, this book demsonstrates the practice of bioinformatics through data skills. Rigorous assessment of data quality and of the effectiveness of tools is the foundation of reproducible and robust bioinformatics analysis. Through open source and freely available tools, you'll learn not only how to do bioinformatics, but how to approach problems as a bioinformatician. Go from handling small problems with messy scripts to tackling large problems with clever methods and tools Focus on high-throughput (or "next generation") sequencing data Learn data analysis with modern methods, versus covering older theoretical concepts Understand how to choose and implement the best tool for the job Delve into methods that lead to easier, more reproducible, and robust bioinformatics analysis

R Programming For Bioinformatics

Author: Robert Gentleman
Publisher: CRC Press
ISBN: 9781420063684
Size: 36.51 MB
Format: PDF, ePub, Mobi
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Due to its data handling and modeling capabilities as well as its flexibility, R is becoming the most widely used software in bioinformatics. R Programming for Bioinformatics explores the programming skills needed to use this software tool for the solution of bioinformatics and computational biology problems. Drawing on the author’s first-hand experiences as an expert in R, the book begins with coverage on the general properties of the R language, several unique programming aspects of R, and object-oriented programming in R. It presents methods for data input and output as well as database interactions. The author also examines different facets of string handling and manipulations, discusses the interfacing of R with other languages, and describes how to write software packages. He concludes with a discussion on the debugging and profiling of R code. With numerous examples and exercises, this practical guide focuses on developing R programming skills in order to tackle problems encountered in bioinformatics and computational biology.

Bioinformatics Programming Using Python

Author: Mitchell L Model
Publisher: "O'Reilly Media, Inc."
ISBN: 9781449382902
Size: 79.24 MB
Format: PDF, Docs
View: 2271
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Powerful, flexible, and easy to use, Python is an ideal language for building software tools and applications for life science research and development. This unique book shows you how to program with Python, using code examples taken directly from bioinformatics. In a short time, you'll be using sophisticated techniques and Python modules that are particularly effective for bioinformatics programming. Bioinformatics Programming Using Python is perfect for anyone involved with bioinformatics -- researchers, support staff, students, and software developers interested in writing bioinformatics applications. You'll find it useful whether you already use Python, write code in another language, or have no programming experience at all. It's an excellent self-instruction tool, as well as a handy reference when facing the challenges of real-life programming tasks. Become familiar with Python's fundamentals, including ways to develop simple applications Learn how to use Python modules for pattern matching, structured text processing, online data retrieval, and database access Discover generalized patterns that cover a large proportion of how Python code is used in bioinformatics Learn how to apply the principles and techniques of object-oriented programming Benefit from the "tips and traps" section in each chapter

Developing Bioinformatics Computer Skills

Author: Cynthia Gibas
Publisher: "O'Reilly Media, Inc."
ISBN: 9781565926646
Size: 29.59 MB
Format: PDF
View: 7615
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Offers a structured approach to biological data and the computer tools needed to analyze it, covering UNIX, databases, computation, Perl, data mining, data visualization, and tailoring software to suit specific research needs.

Genomics And Bioinformatics

Author: Tore Samuelsson
Publisher: Cambridge University Press
ISBN: 1107378338
Size: 11.14 MB
Format: PDF, Docs
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With the arrival of genomics and genome sequencing projects, biology has been transformed into an incredibly data-rich science. The vast amount of information generated has made computational analysis critical and has increased demand for skilled bioinformaticians. Designed for biologists without previous programming experience, this textbook provides a hands-on introduction to Unix, Perl and other tools used in sequence bioinformatics. Relevant biological topics are used throughout the book and are combined with practical bioinformatics examples, leading students through the process from biological problem to computational solution. All of the Perl scripts, sequence and database files used in the book are available for download at the accompanying website, allowing the reader to easily follow each example using their own computer. Programming examples are kept at an introductory level, avoiding complex mathematics that students often find daunting. The book demonstrates that even simple programs can provide powerful solutions to many complex bioinformatics problems.

Beginning Perl For Bioinformatics

Author: James Tisdall
Publisher: "O'Reilly Media, Inc."
ISBN: 9780596550479
Size: 66.73 MB
Format: PDF, Kindle
View: 6088
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With its highly developed capacity to detect patterns in data, Perl has become one of the most popular languages for biological data analysis. But if you're a biologist with little or no programming experience, starting out in Perl can be a challenge. Many biologists have a difficult time learning how to apply the language to bioinformatics. The most popular Perl programming books are often too theoretical and too focused on computer science for a non-programming biologist who needs to solve very specific problems.Beginning Perl for Bioinformatics is designed to get you quickly over the Perl language barrier by approaching programming as an important new laboratory skill, revealing Perl programs and techniques that are immediately useful in the lab. Each chapter focuses on solving a particular bioinformatics problem or class of problems, starting with the simplest and increasing in complexity as the book progresses. Each chapter includes programming exercises and teaches bioinformatics by showing and modifying programs that deal with various kinds of practical biological problems. By the end of the book you'll have a solid understanding of Perl basics, a collection of programs for such tasks as parsing BLAST and GenBank, and the skills to take on more advanced bioinformatics programming. Some of the later chapters focus in greater detail on specific bioinformatics topics. This book is suitable for use as a classroom textbook, for self-study, and as a reference.The book covers: Programming basics and working with DNA sequences and strings Debugging your code Simulating gene mutations using random number generators Regular expressions and finding motifs in data Arrays, hashes, and relational databases Regular expressions and restriction maps Using Perl to parse PDB records, annotations in GenBank, and BLAST output

Data Analysis With Open Source Tools

Author: Philipp K. Janert
Publisher: "O'Reilly Media, Inc."
ISBN: 1449396658
Size: 44.30 MB
Format: PDF, Kindle
View: 2967
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Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications. Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you. Use graphics to describe data with one, two, or dozens of variables Develop conceptual models using back-of-the-envelope calculations, as well asscaling and probability arguments Mine data with computationally intensive methods such as simulation and clustering Make your conclusions understandable through reports, dashboards, and other metrics programs Understand financial calculations, including the time-value of money Use dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situations Become familiar with different open source programming environments for data analysis "Finally, a concise reference for understanding how to conquer piles of data."--Austin King, Senior Web Developer, Mozilla "An indispensable text for aspiring data scientists."--Michael E. Driscoll, CEO/Founder, Dataspora

Practical Computing For Biologists

Author: Steven Harold David Haddock
Publisher: Sinauer Associates Incorporated
ISBN: 9780878933914
Size: 68.55 MB
Format: PDF, ePub
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To help with the increasingly large data sets that many scientists deal with, this book illustrates how to use many freely available computing tools to work more powerfully and effectively. The book was born out of the authors' experiences developing tools for their research and to fix other biologist's computational problems.