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Críticas Practical Computing for Biologists is a clear guide to methods that unlock the power of the personal computer. Although the breadth of subjects covered is certainly an asset of this volume what really makes the book stand out is how well the authors clearly describe each technique and its applicability to biological sciences. It is a great launching point for any necessary further investigation of computational techniques. (Matthew Aiello-Lammens The Quarterly Review of Biology)The book covers a wide range of subjects that truly justifies the title of 'practical computing.' In addition to the usual programming-related topics it also includes a thorough introduction to the programming environment approaches to combining different programs together a description of the basic text manipulation tools such as regular expressions and even an introduction to dealing with digital art and images. As such the book is great value for the money being at least three books in one. (Olga G. Troyanskaya Cell)My copy of Practical Computing for Biologists arrived last week and I've been very impressed. It is a well-written well-paced guide to basic computing skills for scientists and engineers of all stripes (not just biologists). It is beautifully produced: full-color printing and great graphical design make this book a joy to read. If I ever do turn Software Carpentry into a book I might skip the topics PCB covers and just tell people to go and buy it. (Greg Wilson software-carpentry.org)When considering my research and use of time this book has been the most important book I've read in the last year and perhaps the last decade. Striking a perfect balance by guiding you through tutorials and nudging your own self-exploration the book has just enough guided direction to not annoy or overwhelm. It has helped (and is still helping) me to do what I was doing before but more efficiently. (Cyme & Cystidium) Reseña del editor Published by Sinauer Associates an imprint of Oxford University Press. Increasingly scientists find themselves facing exponentially larger data sets and analyses without suitable tools to deal with them. Many biologists end up using spreadsheet programs for most of their data-processing tasks and spend hours clicking around or copying and pasting and then repeating the process for other data files. Practical Computing for Biologists shows you how to use many freely available computing tools to work more powerfully and effectively. The book was born out of the authors' own experience in developing tools for their research and helping other biologists with their computational problems. Although many of the techniques are relevant to molecular bioinformatics the motivation for the book is much broader focusing on topics and techniques that are applicable to a range of scientific endeavors. Twenty-two chapters organized into six parts address these topics (and more; see Contents): * Searching with regular expressions * The Unix command line * Python programming and debugging * Creating and editing graphics * Databases * Performing analyses on remote servers * Working with electronics While most of the concepts and examples apply to any operating system the main narrative focuses on Mac OS X. Where there are differences for Windows and Linux users parallel instructions are provided in the margin and in an appendix. The book is designed to be used as a self-guided resource for researchers a companion book in a course or as a primary textbook. Practical Computing for Biologists will free you from the most frustrating and time-consuming aspects of data processing so you can focus on the pleasures of scientific inquiry. Descripción del libro An essential tool that provides researchers with freedom from the most frustrating and time-consuming aspects of data processing so they can focus on the pleasures of scientific inquiry Contraportada Practical Computing for Biologists shows you how to use many freely available computing tools to work more powerfully and effectively. The book was born out of the authors' own experience in developing tools for their research and helping other biologists with their computational problems. Many of the techniques are relevant to molecular bioinformatics but the scope of the book is much broader covering topics and techniques that are applicable to a range of scientific endeavours.   Twenty-two chapters organized into six parts address the following topics (and more; see Contents): • Searching with regular expressions • The Unix command line • Python programming and debugging • Creating and editing graphics • Databases • Performing analyses on remote servers • Working with electronics While the main narrative focuses on Mac OS X most of the concepts and examples apply to any operating system. Where there are differences for Windows and Linux users parallel instructions are provided in the margin and in an appendix. The book is designed to be used as a self-guided resource for researchers a companion book in a course or as a primary textbook. Practical Computing for Biologists will free you from the most frustrating and time-consuming aspects of data processing so you can focus on the pleasures of scientific inquiry. Biografía del autor Steven H.D. Haddock is a Research Scientist at the Monterey Bay Aquarium Research Institute and adjunct Associate Professor at the University of California Santa Cruz studying bioluminescence and biodiversity of gelatinous zooplankton. He started programming in BASIC on an Apple ][ and began his undergraduate studies in engineering before deciding to change fields. He took this programming background with him to his graduate studies in Marine Biology where he quickly realized the advantages that computing skills offered and felt compelled to help foster these abilities in others. He has developed many utilities and devices for research including instruments to monitor bioluminescence from fireflies a freezer monitoring system a web-based conference registration database and a PCR calculator for smartphones. Casey W. Dunn a Professor at Yale University does research that has a large computational component but always in conjunction with work in the field and lab. His first interest in computers stemmed from building electronics and he further developed his computational skills working in Silicon Valley while an undergraduate. As his data sets grew larger and larger during grad school and his postdoc he found himself reaching back to his computer background more often. In the course of his own research and helping other biologists with their computational challenges he became concerned about the mismatch between training opportunities and the real day-to-day computational problems biologists face.

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