
Bioinformatics encompasses a broad and ever-changing range of activities involved with the management and analysis of data from molecular biology experiments. Despite the diversity of activities and applications, the basic methodology and core tools needed to tackle bioinformatics problems is common to many projects. This unique book provides an invaluable introduction to three of the main tools used in the development of bioinformatics software - Perl, R and MySQL - and explains how these can be used together to tackle the complex data-driven challenges that typify modern biology. These industry standard open source tools form the core of many bioinformatics projects, both in academia and industry. The methodologies introduced are platform independent, and all the examples that feature have been tested on Windows, Linux and Mac OS. Building Bioinformatics Solutions is suitable for graduate students and researchers in the life sciences who wish to automate analyses or create their own databases and web-based tools. No prior knowledge of software development is assumed. Having worked through the book, the reader should have the necessary core skills to develop computational solutions for their specific research programmes. The book will also help the reader overcome the inertia associated with penetrating this field, and provide them with the confidence and understanding required to go on to develop more advanced bioinformatics skills.
This book investigates how researchers can integrate Perl, R, and MySQL to manage and analyze complex biological data sets. The authors, Conrad Bessant, Darren Oakley, and Ian Shadforth, leverage their expertise in computational biology to provide a structured framework for automating laboratory workflows. By focusing on open-source tools, the text aims to lower the barrier to entry for life science researchers who need to build custom databases and analytical pipelines without prior software development experience.
What You Will Find
Scope Limits
Experts and educators frequently cite this text as a foundational resource for graduate students transitioning into computational biology. Readers often note that the prose is accessible for those without a formal computer science background, making it a standard entry point for laboratory-based researchers.
Page Count:
368
Publication Date:
2014-01-01
Publisher:
OUP Oxford
ISBN-10:
0191643203
ISBN-13:
9780191643200
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