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№ на артикул:
154854727
Python Programming for Biology, (Hardcover)
№ на артикул:
154854727
€ 174
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This guide provides a foundation for both newcomers to computer programming and those interested in learning more about computational biology.
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What Stands Out
Comprehensive Coverage
Covers a wide range of bioinformatics topics, ensuring readers gain a solid foundation in applying Python programming to biological data analysis and research.
User-Friendly Approach
Introduces complex concepts in an approachable manner, making it accessible for beginners while still valuable for experienced programmers seeking to enhance their bioinformatics skills.
Practical Examples
Includes real-world applications and case studies that illustrate the practical uses of Python in biology, empowering readers to directly apply learned skills to their own research projects.
Информация за продукта
- Do you have a biological question that could be readily answered by computational techniques, but little experience in programming? Do you want to learn more about the core techniques used in computational biology and bioinformatics? Written in an accessible style, this guide provides a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters guide the reader through: a complete beginners' course to programming in Python, with an introduction to computing jargon; descriptions of core bioinformatics methods with working Python examples; scientific computing techniques, including image analysis, statistics and machine learning. This book also functions as a language reference written in straightforward English, covering the most common Python language elements and a glossary of computing and biological terms. This title will teach undergraduates, postgraduates and professionals working in the life sciences how to program with Python, a powerful, flexible and easy-to-use language.
| Book format | Hardcover |
| Fiction/nonfiction | Non-Fiction |
| Genre | Textbooks |
| Publication date | February, 2015 |
| Pages | 711 |
| Subgenre | Life Sciences |
| Series title | No Series |
| Edition | 1 |
| Publisher | Cambridge University Press |
| Original languages | English |
| Language | English |
| Edu focus | Biology |
| Educational level | College |
| Is collectible | N |
| Binding type | Case Binding |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 7.00 x 1.40 x 9.80 in (17.8 x 3.6 x 24.9 cm) |
| Assembled product weight | 3.35 lb (1.52 kg) |
| Bisac subject heading | Science |
Who Should Buy?
-
Biology Students
Ideal for biology students seeking to learn programming skills applicable in bioinformatics and data analysis.
-
Bioinformatics Professionals
Equips bioinformatics professionals with Python programming techniques for advanced biological data analysis.
-
Self-Learners
Great for self-learners interested in applying Python programming to solve biological problems and enhance their skills.
-
Complete Beginners
Not suitable for individuals without any programming background, as it may be too advanced and technical.
-
Casual Readers
Those looking for light reading or casual information about biology may find this book too technical and dense.
-
Non-Technical Professionals
Non-technical professionals may struggle with the programming aspects and find the content challenging to understand and apply.
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Въпроси на клиенти и отговори
-
въпрос:
Who is this book suitable for?
отговор: It is suitable for beginners, undergraduates, postgraduates, and professionals in the life sciences. -
въпрос:
What programming language does the book focus on?
отговор: The book focuses on Python programming. -
въпрос:
Does the book include practical examples?
отговор: Yes, it includes working Python examples for core bioinformatics methods.
Tim J Stevens All Books Editorial Review
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€ 174
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Характеристики и предимства
- Comprehensive beginners' course in Python programming.
- Accessible writing style suitable for all skill levels.
- Covers core bioinformatics methods with practical examples.
- Includes scientific computing techniques such as image analysis and machine learning.
- Serves as a language reference with essential Python elements.
- Designed for undergraduates, postgraduates, and life science professionals.