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Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools
Go from handling small problems with messy scripts to tackling large problems with clever methods and tools
Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools
Artigo n.º: 417095

Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools

Artigo n.º: 417095

XOF 38692

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O que se Destaca

Open Source Tools
Utilizes accessible, free tools that empower researchers to perform bioinformatics analysis without hefty software costs, enhancing usability and collaboration in academic and professional settings.
Reproducible Research
Teaches methodologies for ensuring research is reproducible, addressing common issues in scientific research reliability, which builds trust and credibility in findings.
Comprehensive Guidance
Provides step-by-step instructions and practical examples, enabling users of all skill levels to efficiently learn bioinformatics, bridging the gap between theory and practical application.

Detalhes do produto

Shop for Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools 1st Edition at Ubuy Guinea-Bissau. Find the best deals on bioinformatics books and tools.
  • Teaches the skills needed to turn large sequencing datasets into reproducible and robust biological findings
  • Emphasizes the practice of bioinformatics through data skills rather than teaching it as a set of workflows
  • Focuses on rigorous assessment of data quality and tool effectiveness for reproducible and robust bioinformatics analysis
  • Covers high-throughput sequencing data analysis using modern methods
  • Provides guidance on choosing and implementing the best tools for bioinformatics tasks
  • Offers methods for achieving easier, more reproducible, and robust bioinformatics analysis
Publisher O'Reilly Media
Publication date August 18, 2015
Edition 1st
Language English
Print length 536 pages
ISBN-10 1449367372
ISBN-13 978-1449367374
Item Weight 2.05 pounds (930 grams)
Dimensions 7 x 1.25 x 9 inches (17.8 x 3.2 x 22.9 cm)

Quem Deverá Comprar?

Suitable For
  • Aspiring Bioinformaticians

    Ideal for newcomers seeking practical skills in bioinformatics and data handling with open-source tools.

  • Researchers in Biology

    Perfect for biologists who want to enhance their research reproducibility and data analysis skills using bioinformatics.

  • Educators and Instructors

    Useful for teaching bioinformatics concepts and methodologies, providing structured guidance for curriculum development.

Not Suitable For
  • Complete Beginners

    Not suitable for individuals with no prior programming or data analysis knowledge, as it assumes some familiarity.

DESCRIÇÃO DO PRODUTO

Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools

Tem alguma Dúvida? Converse connosco

Perguntas e respostas do cliente

  • Pergunta: What is the focus of this book?

    Resposta: The book focuses on teaching practical skills for analyzing large sequencing datasets in the field of bioinformatics.
  • Pergunta: What kind of data does it cover?

    Resposta: It specifically focuses on high-throughput (or next generation) sequencing data.
  • Pergunta: What will I learn from this book?

    Resposta: You will learn how to choose and implement the best tools for bioinformatics analysis, as well as modern data analysis methods.
  • Pergunta: Is this book suitable for beginners?

    Resposta: The book may be a bit dense for beginners, but it provides valuable knowledge and is a good reference.
  • Pergunta: Is the book applicable to real-world work?

    Resposta: Yes, the book covers Unix tools and remote machines, which are directly applicable to real-world work.
  • Pergunta: Does the book emphasize reproducible research?

    Resposta: Yes, the book emphasizes reproducible research and provides good data analysis practices.

Software Development Editorial Review

Bioinformatics Data Skills is highly recommended for scientists with a background in biology looking to get into data analysis. It is a well-written and easy-to-follow book that introduces all the skills needed to work on state-of-the-art NGS data. The author's experience in interacting with beginners is evident in his step-by-step approach. The book covers a wide range of topics, with a good balance of depth. The chapters on Unix tools and remote machines are directly applicable to real-world work. The book emphasizes reproducible research and provides practical knowledge and good data analysis practices. It may be a bit dense for beginners but serves as a valuable reference.

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Prós

  • Readable and concise
  • Step-by-step approach
  • Covers a wide range of topics
  • Applicable to real-world work
  • Emphasizes reproducible research

Contras

  • Middle third of the book might not be relevant for some readers

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