E-raamat: Bioinformatics For Dummies

  • Formaat: 464 pages, illustrations, Contains 1 Digital online
  • Sari: For Dummies S.
  • Ilmumisaeg: 12-Mar-2007
  • Kirjastus: John Wiley & Sons Ltd
  • ISBN-13: 9780470121351
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  • Formaat: 464 pages, illustrations, Contains 1 Digital online
  • Sari: For Dummies S.
  • Ilmumisaeg: 12-Mar-2007
  • Kirjastus: John Wiley & Sons Ltd
  • ISBN-13: 9780470121351

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Were you always curious about biology but were afraid to sit through long hours of dense reading? Did you like the subject when you were in high school but had other plans after you graduated? Now you can explore the human genome and analyze DNA without ever leaving your desktop!

Bioinformatics For Dummies is packed with valuable information that introduces you to this exciting new discipline. This easy-to-follow guide leads you step by step through every bioinformatics task that can be done over the Internet. Forget long equations, computer-geek gibberish, and installing bulky programs that slow down your computer. You’ll be amazed at all the things you can accomplish just by logging on and following these trusty directions. You get the tools you need to:

  • Analyze all types of sequences
  • Use all types of databases
  • Work with DNA and protein sequences
  • Conduct similarity searches
  • Build a multiple sequence alignment
  • Edit and publish alignments
  • Visualize protein 3-D structures
  • Construct phylogenetic trees

This up-to-date second edition includes newly created and popular databases and Internet programs as well as multiple new genomes. It provides tips for using servers and places to seek resources to find out about what’s going on in the bioinformatics world. Bioinformatics For Dummies will show you how to get the most out of your PC and the right Web tools so you’ll be searching databases and analyzing sequences like a pro!

Introduction 1(1)
What This Book Does for You
1(1)
Foolish Assumptions
2(1)
How This Book Is Organized
2(2)
Part I: Getting Started in Bioinformatics
3(1)
Part II: A Survival Guide to Bioinformatics
3(1)
Part III: Becoming a Pro in Sequence Analysis
3(1)
Part IV: Becoming a Specialist: Advanced Bioinformatics Techniques
3(1)
Part V: The Part of Tens
4(1)
Icons Used in This Book
4(1)
Where to Go from Here
4(3)
Part I: Getting Started in Bioinformatics
7(60)
Finding Out What Bioinformatics Can Do for You
9(20)
What Is Bioinformatics?
9(1)
Analyzing Protein Sequences
10(7)
A brief history of sequence analysis
12(1)
Reading protein sequences from N to C
13(1)
Working with protein 3-D structures
14(2)
Protein bioinformatics covered in this book
16(1)
Analyzing DNA Sequences
17(4)
Reading DNA sequences the right way
17(1)
The two sides of a DNA sequence
18(2)
Palindromes in DNA sequences
20(1)
Analyzing RNA Sequences
21(2)
RNA structures: Playing with sticky strands
22(1)
More on nucleic acid nomenclature
23(1)
DNA Coding Regions: Pretending to Work with Protein Sequences
23(3)
Turning DNA into proteins: The genetic code
24(1)
More with coding DNA sequences
25(1)
DNA/RNA bioinformatics covered in this book
26(1)
Working with Entire Genomes
26(3)
Genomics: Getting all the genes at once
27(1)
Genome bioinformatics covered in this book
28(1)
How Most People Use Bioinformatics
29(38)
Becoming an Instant Expert with PubMed/Medline
29(13)
Finding out about a protein by its name
30(2)
Searching PubMed using author's names
32(3)
Searching PubMed using fields
35(3)
Searching PubMed using limits
38(3)
A few more tips about PubMed
41(1)
Retrieving Protein Sequences
42(9)
ExPASy: A prime Internet site for protein information
42(3)
More advanced ways to retrieve protein sequences
45(3)
Retrieving a list of related protein sequences
48(3)
Retrieving DNA Sequences
51(6)
Not all DNA is coding for protein
51(1)
Going from protein sequences to DNA sequences
52(1)
Retrieving the DNA sequence relevant to my protein
53(4)
Using BLAST to Compare My Protein Sequence to Other Protein Sequences
57(5)
Making a Multiple Protein Sequence Alignment with ClustalW
62(5)
Part II: A Survival Guide to Bioinformatics
67(130)
Using Nucleotide Sequence Databases
69(36)
Reading into Genes and Genomes
70(3)
Prokaryotes: Small bugs, simple genes
70(2)
Eukaryotes: Bigger bugs, complex genes
72(1)
Making Use (and Sense) of GenBank
73(13)
Making sense of the GenBank entry of a prokaryotic gene
73(5)
Making sense of the GenBank entry of an eukaryotic mRNA
78(1)
Making sense of a GenBank eukaryotic genomic entry
79(5)
Working with related GenBank entries
84(1)
Retrieving GenBank entries without accession numbers
85(1)
Using a Gene-Centric Database
86(2)
Working with Whole-Genome Databases
88(9)
Working with complete viral genomes
89(3)
Working with complete bacterial genomes
92(2)
More bacterial genomics at TIGR
94(2)
Microbes from the environment at DoE
96(1)
Exploring the Human Genome
97(8)
Finding out about the Ensembl project
98(7)
Using Protein and Specialized Sequence Databases
105(24)
From Translated ORFs to Mature Proteins
107(3)
ORFs: What you see is NOT what you get
107(2)
A personal final destination for each protein
109(1)
A combinatorial diversity of folds and functions
109(1)
Reading a Swiss-Prot Entry
110(13)
Deciphering the EGFR Swiss-Prot entry
110(1)
General information about the entry
111(1)
Name and origin of the protein
112(2)
The References
114(1)
The Comments
114(2)
The Cross-References
116(2)
The Keywords
118(1)
The Features
119(4)
Finally, the sequence itself
123(1)
Finding Out More about Your Protein
123(6)
Finding out more about ``modified amino acids
124(1)
Some advanced biochemistry sites
125(1)
Finding out more about biochemical pathways
125(1)
Finding out more about protein structures
126(1)
Finding out more about major protein families
127(2)
Working with a Single DNA Sequence
129(30)
Catching Errors Before It's Too Late
130(4)
Removing vector sequences
130(3)
Cases when you shouldn't discard your sequence
133(1)
Computing/Verifying a Restriction Map
134(1)
Designing PCR Primers
135(3)
Analyzing DNA Composition
138(7)
Establishing the G+C content of your sequence
138(1)
Counting words in DNA sequences
139(1)
Counting long words in DNA sequences
140(2)
Experimenting with other DNA composition analyses
142(1)
Finding internal repeats in your sequence
142(3)
Identifying genome-specific repeats in your sequence
145(1)
Finding Protein-Coding Regions
145(8)
ORFing your DNA sequence
146(2)
Analyzing your DNA sequence with GeneMark
148(1)
Finding internal exons in vertebrate genomic sequences
149(2)
Complete gene parsing for eukaryotic genomes
151(1)
Analyzing your sequence with GenomeScan
151(2)
Assembling Sequence Fragments
153(4)
Managing large sequencing projects with public software
154(1)
Assembling your sequences with CAP3
155(2)
Beyond This
Chapter
157(2)
Working with a Single Protein Sequence
159(38)
Doing Biochemistry on a Computer
160(6)
Predicting the main physico-chemical properties of a protein
161(3)
Interpreting ProtParam results
164(2)
Digesting a protein in a computer
166(1)
Doing Primary Structure Analysis
166(8)
Looking for transmembrane segments
168(6)
Looking for coiled-coil regions
174(1)
Predicting Post-Translational Modifications in Your Protein
174(6)
Looking for PROSITE patterns
175(2)
Interpreting ScanProsite results
177(3)
Finding Known Domains in Your Protein
180(14)
Choosing the right collection of domains
182(1)
Finding domains with InterProScan
183(2)
Interpreting InterProScan results
185(2)
Finding domains with the CD server
187(2)
Interpreting and understanding CD server results
189(1)
Finding domains with Motif Scan
190(4)
Discovering New Domains in Your Proteins
194(1)
More Protein Analysis for Free over the Internet
194(3)
Part III: Becoming a Pro in Sequence Analysis
197(130)
Similarity Searches on Sequence Databases
199(36)
Understanding the Importance of Similarity
200(1)
The Most Popular Data-Mining Tool Ever: Blast
201(18)
Blasting protein sequences
201(8)
Understanding your Blast output
209(7)
Blasting DNA sequences
216(2)
The Blast way of doing things
218(1)
Controlling Blast: Choosing the Right Parameters
219(7)
Controlling the sequence masking
220(3)
Changing the Blast alignment parameters
223(1)
Controlling the Blast output
224(2)
Making Blast Iterative with PSI-Blast
226(5)
PSI-Blasting protein sequences
226(2)
Avoiding mistakes when running PSI-Blast
228(2)
Discovering and using protein domains with Blast and PSI-Blast
230(1)
Similarity Searches for Free over the Internet
231(4)
Comparing Two Sequences
235(30)
Making Sure You Have the Right Sequences and the Right Methods
236(3)
Choosing the right sequences
236(1)
Choosing the right method
237(2)
Making a Dot Plot
239(15)
Choosing the right dot-plot flavor
240(1)
Using Dotlet over the Internet
241(8)
Doing biological analysis with a dot plot
249(5)
Making Local Alignments over the Internet
254(7)
Choosing the right local-alignment flavor
255(1)
Using Lalign to find the ten best local alignments
256(2)
Interpreting the Lalign output
258(3)
Making Global Alignments over the Internet
261(1)
Using Lalign to Make a Global Alignment
262(1)
Aligning Proteins and DNA
262(1)
Free Pairwise Sequence Comparisons over the Internet
262(3)
Building a Multiple Sequence Alignment
265(38)
Finding Out if a Multiple Sequence Alignment Can Help You
266(4)
Identifying situations where multiple alignments do not help
267(1)
Helping your research with multiple sequence alignments
267(3)
Choosing the Right Sequences
270(11)
The kinds of sequences you're looking for
271(4)
Gathering your sequences with online Blast servers
275(6)
Choosing the Right Method of Multiple Sequence Alignment
281(10)
Using ClustalW
282(5)
Aligning sequences and structures with Tcoffee
287(4)
Crunching large datasets with MUSCLE
291(1)
Interpreting Your Multiple Sequence Alignment
291(6)
Recognizing the good parts in a protein alignment
292(2)
Taking your multiple alignment further
294(3)
Comparing Sequences That You Can't Align
297(2)
Making multiple local alignments with the Gibbs sampler
298(1)
Searching conserved patterns
299(1)
Internet Resources for Doing Multiple Sequence Comparisons
299(4)
Making multiple alignments with ClustalW around the clock
300(1)
Finding your favorite alignment method
300(1)
Searching for motifs or patterns
301(2)
Editing and Publishing Alignments
303(24)
Getting Your Multiple Alignment in the Right Format
305(8)
Recognizing the main formats
307(1)
Working with the right format
307(2)
Converting formats
309(3)
Watching out for lost data
312(1)
Using Jalview to Edit Your Multiple Alignment Online
313(6)
Starting Jalview
314(2)
Editing a group of sequences
316(2)
Useful features of Jalview
318(1)
Saving your alignment in Jalview
318(1)
Preparing Your Multiple Alignment for Publication
319(4)
Using Boxshade
319(3)
Logos
322(1)
Editing and Analyzing Multiple Sequence Alignments for Free over the Internet
323(4)
Finding multiple-sequence-alignment editors
323(1)
Finding tools to interpret your multiple sequence alignment
324(1)
Finding tools for beautifying your multiple alignments
325(2)
Part IV: Becoming a Specialist: Advanced Bioinformatics Techniques
327(76)
Working with Protein 3-D Structures
329(24)
From Primary to Secondary Structures
330(6)
Predicting the secondary structure of a protein sequence
330(4)
Predicting additional structural features
334(2)
From the Primary Structure to the 3-D Structure
336(14)
Retrieving and displaying a 3-D structure from a PDB site
337(3)
Guessing the 3-D structure of your protein
340(3)
Looking at sequence features in 3-D
343(7)
Beyond This
Chapter
350(3)
Finding proteins with similar shapes
350(1)
Finding other PDB viewers
350(1)
Classifying your PDB structure
351(1)
Doing homology modeling
351(1)
Folding proteins in a computer
351(1)
Threading sequences onto PDB structures
351(1)
Looking at structures in movement
352(1)
Predicting interactions
352(1)
Working with RNA
353(18)
Predicting, Modeling and Drawing RNA Secondary Structures
354(1)
Using Mfold
355(7)
Interpreting mfold results
359(2)
Forcing interaction in mfold
361(1)
Searching Databases and Genomes for RNA Sequences
362(5)
Finding tRNAs in a genome
363(1)
Using PatScan to look for RNA patterns
363(4)
Finding the ``New'' RNAs: miRNAs and siRNAs
367(1)
Doing RNA Analysis for Free over the Internet
368(3)
Studying evolution with ribosomal RNA
369(1)
Finding the small, non-coding RNA you need
369(1)
Generic RNA resources
370(1)
Building Phylogenetic Trees
371(32)
Finding Out What Phylogenetic Trees Can Do for You
372(1)
Preparing Your Phylogenetic Data
373(10)
Choosing the right sequences for the right tree
374(6)
Preparing your multiple sequence alignment
380(3)
Building the Kind of Tree You Need
383(17)
Computing your tree
383(15)
Knowing what's what in your tree
398(1)
Displaying your phylogenetic tree
399(1)
Doing Phylogeny for Free over the Internet
400(3)
Finding online resources
400(1)
Finding generic resources
401(1)
Collections of orthologous genes
402(1)
Part V: The Part of Tens
403(14)
The Ten (Okay, Twelve) Commandments for Using Servers
405(6)
Keep in Mind: Your Data Is Never Secure on the Web
406(1)
Remember the Server, the Database, and the Program Version You Used
406(1)
Write Down the Sequence-Identification Numbers
407(1)
Write Down the Program Parameters
407(1)
Save Your Internet Results the Right Way
407(1)
Use E-Values
408(1)
Make Sure You Can Trust Your Alignments
408(1)
Use Different Programs to Check Borderline Results
409(1)
Stay Away from Unpublished Methods!
409(1)
Databases Are Not Like Good Wine
409(1)
Just Because It Looks Free Doesn't Mean It Is Free
410(1)
Biting the Bullet at the Right Time
410(1)
Some Useful Bioinformatics Resources
411(6)
Ten Major Databases
411(1)
Ten Major Bioinformatics Software Programs
412(2)
Ten Major Resource Locators
414(1)
Some Places to Find Out What's Really Going On
415(2)
Index 417


Jean-Michel Claverie is Professor of Medical Bioinformatics at the School of Medicine of the Universite de la Mediterranee, and a consultant in genomics and bioinformatics. He is the founder and current head of the Structural & Genomic Information Laboratory, located in Marseilles, a sunny city on the Mediterranean coast of France. Using science as a pretext to travel, Jean-Michel has held positions in Paris (France), Sherbrooke (PQ, Canada), the Salk Institute (La Jolla, CA), the Pasteur Institute (Paris), Incyte pharmaceutical (Palo Alto, CA); and the National Center for Biotechnology Information (Bethesda, MD). He has used computers in biology since the early days -- his Ph.D. work involved modeling biochemical reactions by programming an 8K Honeywell 516 computer right from the console switches! Although he has no clear recollection of it, he has been credited with introducing the French word "bioinformatique" in the late eighties, before involuntarily coining the catchy "bioinformatics" by mistranslating it while giving a talk in English! Jean-Michel's current research interests are in microbial and structural genomics, and in the development of bioinformatic methods for the prediction of gene function. He is the author or coauthor of more than 150 scientific publications, and a member of numerous international review panels and scientific councils. In his spare time, he enjoys the relaxed pace of life in Marseilles, with his wife Chantal and their two sons, Nicholas and Raphael. Cedric Notredame is a researcher at the French National Centre for Scientific Research. Cedric has used and abused the facilities offered by science to wander around Europe. After a Ph.D. at EMBL (Heidelberg, Germany) and at the European Bioinformatics Institute (Cambridge, UK) under the supervision of Des Higgins (yes, the ClustalW guy), Cedric did a post-doc at the National Institute of Medical Research (London, UK), in the lab of Willie Taylor and under the supervision of Jaap Heringa. He then did a post-doc in Lausanne (Switzerland) with Phillip Bucher, and remained involved with the Swiss Institute of Bioinformatics for several years. Having had his share of rain, snow, and wind, Cedric has finally settled in Marseilles, where the sun and the sea are simply warmer than any other place he has lived in. Cedric dedicates most of his research to the multiple sequence alignment problem and its many applications in biology. His friends claim that his entire life (past, present, future) is somehow stuffed into the T-Coffee multiple-sequence alignment package. When he is not busy dismantling T-Coffee and brewing new sequences, Cedric enjoys life in the company of his wife, Marita.