Practical Computing for Biologists

Regular price €134.99
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
A01=Casey W. Dunn
A01=Steven H. D. Haddock
Age Group_Uncategorized
Age Group_Uncategorized
Author_Casey W. Dunn
Author_Steven H. D. Haddock
automatic-update
Category1=Non-Fiction
Category=PSA
computation
COP=United States
Delivery_Delivery within 10-20 working days
eq_bestseller
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
Language_English
PA=Available
Price_€100 and above
PS=Active
softlaunch

Product details

  • ISBN 9780878933914
  • Weight: 1197g
  • Dimensions: 230 x 193mm
  • Publication Date: 05 Nov 2010
  • Publisher: Oxford University Press Inc
  • Publication City/Country: US
  • Product Form: Paperback
  • Language: English
Secure checkout Fast Shipping Easy returns
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.
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.

More from this author