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Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools
86% of respondents would recommend this to a friend
SAR 215
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Go from handling small problems with messy scripts to tackling large problems with clever methods and tools
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What Stands Out
Product Details
- 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) |
Who Should Buy?
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Aspiring Bioinformaticians
Ideal for newcomers seeking practical skills in bioinformatics and data handling with open-source tools.
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Researchers in Biology
Perfect for biologists who want to enhance their research reproducibility and data analysis skills using bioinformatics.
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Educators and Instructors
Useful for teaching bioinformatics concepts and methodologies, providing structured guidance for curriculum development.
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Complete Beginners
Not suitable for individuals with no prior programming or data analysis knowledge, as it assumes some familiarity.
Product Description
Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools
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Features & Benefits
- Learn practical skills for turning large sequencing datasets into reproducible and robust biological findings
- Focus on high-throughput sequencing data
- Learn data analysis with modern methods
- 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
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