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Chapman & Hall/CRC
18 March 2014
Biology, life sciences; Web programming
Take Control of Your Data and Use Python with Confidence Requiring no prior programming experience, Managing Your Biological Data with Python empowers biologists and other life scientists to work with biological data on their own using the Python language. The book teaches them not only how to program but also how to manage their data. It shows how to read data from files in different formats, analyze and manipulate the data, and write the results to a file or computer screen.

The first part of the text introduces the Python language and teaches readers how to write their first programs. The second part presents the basic elements of the language, enabling readers to write small programs independently. The third part explains how to create bigger programs using techniques to write well-organized, efficient, and error-free code. The fourth part on data visualization shows how to plot data and draw a figure for an article or slide presentation. The fifth part covers the Biopython programming library for reading and writing several biological file formats, querying the NCBI online databases, and retrieving biological records from the web. The last part provides a cookbook of 20 specific programming recipes, ranging from secondary structure prediction and multiple sequence alignment analyses to superimposing protein three-dimensional structures.

Tailoring the programming topics to the everyday needs of biologists, the book helps them easily analyze data and ultimately make better discoveries. Every piece of code in the text is aimed at solving real biological problems.
By:   Allegra Via (University of Rome La Sapienza Italy), Kristian Rother (Adam Mickiewicz University, Poznan, Poland), Anna Tramontano (University of Rome La Sapienza, Italy)
Imprint:   Chapman & Hall/CRC
Country of Publication:   United States
Volume:   52
Dimensions:   Height: 235mm,  Width: 156mm,  Spine: 33mm
Weight:   816g
ISBN:   9781439880937
ISBN 10:   143988093X
Series:   Chapman & Hall/CRC Computational Biology Series
Pages:   560
Publication Date:   18 March 2014
Audience:   College/higher education ,  Professional and scholarly ,  Primary ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active

Reviews for Managing Your Biological Data with Python

Having read Managing Your Biological Data with Python brings back memories of the times I started writing my first lines of code nearly a decade ago. As a beginning structural biologist without any coding experience, this book would have been a welcome companion to quickly get me started on my bioinformatical projects with Python. It is this, often pragmatic, attitude scientists have towards programming that makes Python the language of choice for many. A clear syntax, powerful build-in functions and a lively ecosystem of user contributed modules allow you to do advanced things with only little lines of code. The book introduces you to the basic principles of programming in Python using the many build-in functions. It does so using practical examples that you can start using right away in your day-to-day research. Python's modular design principles could even be seen in the organization of this book. If you have never written a line of code in your life, the first chapters are indispensable to teach you basic coding principles but if you have some experience, you can safely skip these. I would however, recommend to read the ones introducing the build-in functions. It never hurts to refresh your memory on the many powerful build-ins Python actually has; I certainly forgot about one or two of them. Working your way through the first chapters will help you get comfortable with Python and lay the foundation for writing more advanced programs in the remaining chapters. These chapters introduce some of the powerful community contributed Python modules that make your life as a biologist a whole lot easier. Again, the example code introducing these modules is of high practical value and together with the coding recipes in the 'cookbook' chapter they provide a solid blueprint for you to build your own code upon. I'm confident that reading Managing Your Biological Data with Python will quickly allow you to get the most out of your data and start answering those trilling scientific questions you have, and do all of that while having fun. -Marc van Dijk, Structural biologist, bioinformaticien, and eScience entrepreneur, Bijvoet Center for Biomolecular Research, Utrecht University, The Netherlands For many biologists faced with computational challenges, Python has become the language of choice, due to its power, elegance, and simplicity. Managing Your Biological Data with Python by Allegra Via et al. teaches Python using biological examples and discusses important Python-driven applications, such as PyMol and Biopython. The book is an excellent resource for any biologist needing relevant programming skills. -Thomas Hamelryck, Associate Professor, Bioinformatics Center, University of Copenhagen, Denmark Biological data volumes are growing rapidly as high-throughput technologies (e.g., DNA microarrays or DNA/RNA sequencing) improve. Managing and analyzing biological data are becoming more demanding and the application of programming techniques has simply become a standard. Managing Your Biological Data with Python is one of very few user-friendly books for biologists. It is amazing how clearly authors explain the possible applications of Python for data management (parsing data records, filtering and sorting data) and data visualization (also using the Python interface to R). The book also offers the description of modular programming, which is simply excellent! It guides readers from writing simple functions through writing classes to building program pipelines-everything according to Python coding standards and in an easy-to-follow way. This is absolutely the best book to start learning Python. Intermediate Python users can use this book to learn some new tricks that they could implement in their own code. I can highly recommend this book to researchers, students, and their lecturers. -Dr. Barbara Uszczynska, Centre de Regulacio Genomica (CRG), Barcelona, Spain


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