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Practical Computing for Biologists
PDF Download Practical Computing for Biologists
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Product details
Paperback: 538 pages
Publisher: Sinauer Associates is an imprint of Oxford University Press; First edition (November 5, 2010)
Language: English
ISBN-10: 0878933913
ISBN-13: 978-0878933914
Product Dimensions:
9 x 1 x 7.5 inches
Shipping Weight: 2.5 pounds (View shipping rates and policies)
Average Customer Review:
4.6 out of 5 stars
53 customer reviews
Amazon Best Sellers Rank:
#75,403 in Books (See Top 100 in Books)
Update:THIS BOOK MADE ME SHINE!One of the exercises in the book involves using building a program using regular expressions to modify the format of lat/lon data into a .kml-readable format.Guess what my employer asked me to do today?Yup, manually reformat hundreds of lines of lat/lon data.It took me 20 minutes instead of tedious hours, and I was paid for completion of the job, not the hours.In science, it is all about efficiency and building a better mouse-trap. This book teaches you all the great shortcuts to stand out in a competitive field of study.THANK YOU PCfB!!!!!My Background:I am a biochemistry and molecular biology graduate who is learning BioPy and R to aid in my ability to process and understand large data sets. I've been reading books on python and bioinformatics, but they are often either too cryptic or too basic. Until I found PCfB, I couldn't find a book that got to the real meat of bioinformatics and biological data processing/management.Review:If you are pursuing higher education in science, buy this book. Seriously, put this book into your cart now.Now that advanced computer skills are in great demand by employers in scientific disciplines, I really think a course involving this material should be mandatory in any undergraduate chemistry or biology department. But it isn't, so buy this book and catch up. This is the information they should have taught you in college.PCfB is probably best for people who have a basic understanding of computers. The book is neither written for experts nor for novices and fits well at the college level. It provides sufficient detail and complex examples without interjecting excess esoteric programming theory.The only downside is that the book is catered towards OSX/UNIX, but to be fair, the authors include how to run commands on windows and linux.
This is an invaluable text for anyone looking to demystified computing. While the examples tend to be biological, for instance dealing with DNA sequences or specimen collection data, I think this textbook will be useful to readers in many different fields of science. In fact, a lot of the text focuses on data acquisition, organization, and management, and is applicable to readers from a variety of fields.This book was recommended to me by a number of biology graduate students that used in it seminar-style courses on bioinformatics. I had no previous experience with programming and was pretty intimidated by programming and computing in general. However, this book helped me get over that fear quickly! It builds a strong foundation in a variety of computational methods (particularly programming in python). With this foundation I was able to take advantage of a lot of online resources that were previously beyond my understanding. In this book, I quickly learned a number of basic strategies for data collection and analysis that would have saved me weeks of work had I known how to employ them earlier in my graduate career. I'm glad I know them now and I look forward to building on the skills I developed with this book!
This is one of the most valuable and useful books that I have read in a very long time. This book is also extremely timely - given how reliant on computers the analysis of biological data is becoming. The authors clearly and concisely walk the reader through a broad range of extremely useful computational processes that will increase the efficiency of how any biologist stores, analyzes, and/or manipulates their data. Most of my colleagues know that they could be using their computers, and analyzing their data, more efficiently; but many do not know where to start, or are intimidated by the vast "computer programming" section of their local bookstore. This book acts as an excellent intermediate step - providing clear (and biologically relevant) examples of how a few key skills can immediately alter daily tasks. The authors then point the reader in the necessary direction for those who wish to learn more. Briefly, some topics that I found particularly helpful were: (1) the use of regular expressions to quickly modify text files (who hasn't suffered through manually doing this to convert the output from one program to the input of another?); (2) the fairly extensive introduction to Python programming and some of its uses; (3) the friendly introduction to MySQL (which can otherwise be very intimidating); and (4) the information on vector art. I also appreciate that the authors focused on Open Source programs; which makes all of the examples/programs available to anyone. I would highly recommend this book to all biologists - full stop. I also want to thank the authors for writing it - it has been a huge help to me, and couldn't have come at a better time.
Great book for ramping up your computational skills. It covers a lot of powerful tools in a very straightforward and easy to digest manner. As a biological researcher, this book has helped me approach raw data more efficiently and streamline redundant processes. I especially liked the sections on handling text files and command line operations. I wish the Python chapters were updated to the latest version, this is the only reason my review is not 5 stars. I would recommend this book to any researchers tired of relying on pre-packaged software suites dictating their experimental decision making.
If, like me, you're getting into bioinformatics mid-career, this book is a simply and straightforward guide to the most essential tools you'll need, like basic linux and handling text files. It has more advanced chapters that get into programming. Start with this book and some good ones on R!
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