Computational biology : a hypertextbook

211 Pages·2018·27.278 MB·English

by  Scott Theodore Kelley, Dennis Didulo

COMPUTATIONAL
BIOLOGY
A HYPERTEXTBOOK

SCOTT T. KELLEY
Department of Biology
San Diego State University
San Diego, California
AND
DENNIS DIDULO
Becton, Dickinson and Company
San Diego, California
COMPUTATIONAL
BIOLOGY
A HYPERTEXTBOOK
Washington, DC
Copyright © 2018 American Society for Microbiology. All rights reserved.
No part of this publication may be reproduced or transmitted in
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Library of Congress Cataloging-i n-P ublication Data
Names: Kelley, Scott T. (Scott Theodore), author. |
Didulo, Dennis, author.
Title: Computational biology : a hypertextbook / Scott T. Kelley, Department
of Biology, San Diego State University, San Diego, California, and Dennis
Didulo, Becton, Dickinson and Company, San Diego, California.
Description: Washington, DC : ASM Press, [2018] | Includes index.
Identifiers: LCCN 2017051454 (print) | LCCN 2017052307 (ebook) | ISBN
9781683670032 (ebook) | ISBN 9781683670025 (pbk.)
Subjects: LCSH: Computational biology.
Classification: LCC QH324.2 (ebook) | LCC QH324.2 .K45 2018 (print) | DDC
570.285--dc23
LC record available at https://lccn.loc.gov/2017051454
All Rights Reserved
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Online: http:// www . asmscience . org
To Kina and Aidan, my wond erf ul and supp orti ve fami l y.
And to my brother Brian, who selfl essly don ated his kidn ey, witho ut
which I would not have had the ene rgy
to write this book.

CONTENTS
Preface ix
For the Instructor xi
For the Student xiii
Acknowl edgments xiv
About the Authors xv
CHAPTER –1 Getting Started 1
CHAPTER 00 Introduction 5
Activity 0.1: Biological Databases and Data Storage 20
CHAPTER 01 BLAST 31
Activity 1.1: BLAST Algorithm 36
CHAPTER 02 Protein Analy sis 47
Activity 2.1: Hydrophobicity Plotting 52
Activity 2.2: Protein Secondary Structure Prediction 58
CHAPTER 03 Sequence Alignment 67
Activity 3.1: Dynamic Programming 74
CHAPTER 04 Patterns in the Data 91
Activity 4.1: Protein Sequence Motifs 94
Activity 4.2: Position-S pecific Weight Matrices 102
CHAPTER 05 RNA Structure Prediction 111
Activity 5.1: RNA Structure Prediction 118
CHAPTER 06 Phyloge ne tics 133
Activity 6.1: Phyloge ne tic Analy sis 140
CHAPTER 07 Probability: All Mutations are not Equal (-ly Probable) 157
Activity 7.1: G enerating PAM and BLOSUM Substitution
Matrices 163
CHAPTER 08 Bioinformatics Programming: A Primer 179
Index 191

PREFACE
T
his textb ook is a hypertextbook. Half of the textb ook mat er ial lies bet ween
the pages of this book and the other half on the Int ern et. It seems nat ur al
that a hypertextbook, which comb ines print and onl ine apps for mob ile tech-
nolo gy, would be a great way to learn the bas ics of bioinformatics, which
uses in for mat ics (com pu ta tional) the ory to study bi o log i cal da ta.
This book was born out of a mix of nec ess ity and ins pir at ion.1 The ne ces sity
came from the dearth of bioinformatics ins truct ional mat er ia ls app rop ria te for my
com bi na tion of bi ol ogy stu dents, with lit tle or no com puter back ground,2 and
comp uter scie nce stud ents, who were int ere sted in the field but had lit tle und er-
standi ng of bio lo gy. The need bec ame acute when I learned that my fa vori te bio-
informatics lab manu al, Bioinformatics for Dummies (BFD3), would no long er be
upd ated. BFD was a great lab manu al for learni ng how to perf orm bas ic bioinfor-
matics data analy sis. This book did not exp lain the princ ip les beh ind the alg o-
rithms, but I could cover those duri ng lect ures. BFD was clear and fun to read and
pro vided prac ti cal skills for bi ol o gists and oth ers look ing to an a lyze data. Unfortu-
nately, the most rec ent vers ion was printed in 2007!
I kept usi ng the old edit ion of BFD for some time, but event ua lly the tut or ia ls
bec ame obs ol ete and the stud ents took long er and long er to comp lete the ex er-
cises. In fact, sev eral pass ages of BFD were obs ol ete a few months af ter the
book was printed. Bioinformatics webs ites are cons tantly changi ng, inc ludi ng
their des igns and the URL links, and somet imes the pages thems elves disa pp ear
alt og ether. Since I beg an writi ng this book, two of the webs ites I teach in the book
and on line ma te ri als changed sig nifi cantly, and one dis ap peared al to geth er.
This led to my origi n al ins pir at ion for the hyp er- part of this hypertextbook.
What if I made my own bioinformatics tut or ia ls and samp le test data for com-
monly used analy sis tools onl ine in easi ly upd ated fil es? That way, when a link
changed or the prog ramm ers moved a rad io but ton around, I could easi ly alt er the
tut or ial to refl ect these changes in real time. Students would not have to wait for
a new vers ion of a book to have an acc ur ate tut or ia l.
The next ins pir at ion arose from my use of pap er-based puzz les and probl ems to
teach the bioinformatics alg or ithms. The probl ems I taught in class, comb ined with
ix