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Mastering Python for Bioinformatics: How to Write Flexible, Documented, Tested Python Code for Research Computing
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Mastering Python for Bioinformatics: How to Write Flexible, Documented, Tested Python Code for Research Computing 1st Edition
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What Stands Out
Λεπτομέρειες προιόντος
- Leatherbound edition of Werken. Volume n.s. no.53 1889
- Language: Dutch
- Reprinted from 1889 edition with no changes to the original text
- Illustrations and index included in black and white
- Sewn binding for longer life, resulting in a durable type of binding
- 600 pages, handcrafted with additional 10 days required for processing
| Publisher | O'Reilly Media |
| Publication date | June 15, 2021 |
| Edition | 1st |
| Language | English |
| Print length | 454 pages |
| ISBN-10 | 1098100883 |
| ISBN-13 | 978-1098100889 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 7 x 1 x 9 inches (17.8 x 2.5 x 22.9 cm) |
Who Should Buy?
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Bioinformatics Researchers
Ideal for researchers seeking to improve their programming skills for bioinformatics applications and computational biology.
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Beginner Programmers
Beneficial for novices who want to learn Python while applying it to biological data analysis and research.
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Academic Instructors
Great resource for professors who teach bioinformatics and need a structured approach to programming with Python.
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Advanced Programmers
Experienced developers may find the content too basic and not sufficiently challenging for their skill level.
ΠΕΡΙΓΡΑΦΗ ΤΟΥ ΠΡΟΪΟΝΤΟΣ
Mastering Python for Bioinformatics: How to Write Flexible, Documented, Tested Python Code for Research Computing
About This Item
Are you an aspiring bioinformatician looking to enhance your programming skills? Look no further than the "Mastering Python for Bioinformatics: How to Write Flexible, Documented, Tested Python Code for Research Computing 1st Edition". This comprehensive book is a must-have for anyone interested in leveraging the power of Python programming in the field of bioinformatics. Packed with practical examples and step-by-step guidance, it equips you with the skills needed to write efficient, flexible, and well-documented Python code. Whether you're a beginner or have some experience in Python, this book caters to all skill levels. It starts with the basics, introducing you to the Python language and its syntax.
From there, it dives into more advanced topics, such as working with bioinformatics-specific libraries, data analysis, and statistical analysis. What sets this book apart from others is its focus on research computing. You'll learn how to apply Python programming to solve real-world bioinformatics problems, making it an invaluable resource for those working in the field of genomics, computational biology, and molecular biology research. With this book as your guide, you'll gain a solid understanding of how Python can be used to analyze and manipulate large datasets, perform complex calculations, and visualize data. The clear and concise explanations, along with the numerous code examples, make it easy to follow along and apply the concepts to your own projects. Whether you're a bioinformatics student, a researcher, or a professional in the field, "Mastering Python for Bioinformatics" will take your Python programming skills to the next level.
Embrace the power of Python and unlock a world of possibilities in bioinformatics research today.
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Software Development Editorial Review
**** "Mastering Python for Bioinformatics" is a comprehensive guide designed for individuals looking to enhance their programming skills in bioinformatics. The book is structured into two key sections: the first two-thirds tackle 14 representative bioinformatics challenges sourced from the Rosalind.info platform. These challenges focus on critical tasks that bioinformaticians often encounter, such as data transformation and motif identification. One notable strength of this book is its emphasis on understanding the rationale behind the coding solutions, rather than merely providing the 'how-to' instructions. This approach not only demonstrates effective coding techniques but also equips readers with knowledge about common pitfalls to avoid in their programming journey. The latter third of the book shifts towards the practical assembly of complete programs, emphasizing the creation of useful applications from bioinformatics data. This section adds significant value, illustrating the transition from solving isolated problems to developing comprehensive software solutions suited for broader use. Additionally, appendices covering testing and documentation practices enrich the reader's programming toolkit, although these sections are less centered on bioinformatics specifics. Targeted towards readers who already possess some command-line proficiency and an understanding of Python syntax, this book provides a sufficient refresher on relevant biological concepts for those with a basic background in biology or genetics. However, complete novices in either programming or biology may find it beneficial to reinforce their knowledge beforehand. In conclusion, "Mastering Python for Bioinformatics" serves as an invaluable resource for bioinformatics students and professionals alike. It is recommended as a must-have reference in any bioinformatics laboratory and is structured to support both thorough learning and practical problem-solving. **
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Πλεονεκτήματα
- Comprehensive coverage of bioinformatics challenges.
- Focuses on understanding the reasoning behind coding solutions.
- Valuable for both beginner and intermediate programmers.
- Includes practical programming applications, enhancing real-world usability.
- Additional resources on testing and documentation.
Μειονεκτήματα
- Some code examples may contain errors.
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Χαρακτηριστικά & Πλεονεκτήματα
- Exploit the best parts of Python to solve problems in biology
- Learn the latest Python features and tools for creating documented and tested programs
- Tackle challenges in Rosalind, a problem-solving platform for learning bioinformatics and programming
- Create command-line Python programs to document and validate parameters
- Address bioinformatics ideas using Python data structures and modules such as Biopython
- Use regular expressions and higher-order functions in Python to find patterns of text and streamline workflows
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