Introductory bioinformatics:
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Norderstedt
Books on Demand
2009
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XIV, 246 S. Ill., graph. Darst. 220 mm x 170 mm, 457 gr. |
| ISBN: | 9783837051896 |
Staff View
MARC
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| 245 | 1 | 0 | |a Introductory bioinformatics |c Stefanie Hartmann ; Joachim Selbig |
| 264 | 1 | |a Norderstedt |b Books on Demand |c 2009 | |
| 300 | |a XIV, 246 S. |b Ill., graph. Darst. |c 220 mm x 170 mm, 457 gr. | ||
| 336 | |b txt |2 rdacontent | ||
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| 999 | |a oai:aleph.bib-bvb.de:BVB01-017989024 | ||
Record in the Search Index
| _version_ | 1804139919045558272 |
|---|---|
| adam_text | Contents
I
First
things first: assembling your toolkit
1
1
What is a gene?
3
1.1
Before the double-helix
............................... 3
1.1.1
It started with peas
............................... 3
1.1.2 ...
and continued with flies
......................... 4
1.1.3
One gene
-
one enzyme
...........................
б
1.1.4
It s the
DNA!................................ 7
1.2
The famous double helix
.............................. 8
1.2.1
The flow of information
........................... 10
1.3
Hypothetical proteins
................................ 13
1.4
Review of terms
................................... 15
1.5
References
...................................... 16
2
Protein structure
17
2.1
Twenty
amino
acids
................................. 18
2.2
Protein structure
................................... 20
2.3
Describing protein structure
............................. 23
v
2.4 Evolution
of protein structure
............................ 25
2.4.1
Structures in the twilight
.......................... 26
2.5
Review of terms
................................... 28
2.6
References
......................................
29
3
Speedy and efficient data analysis
31
3.1
Algorithms
...................................... 31
3.1.1
Do you know a short-cut?
.......................... 33
3.2
Graphs
........................................ 36
3.2.1
Graph algorithms
.............................. 37
3.3
Machine learning
.................................. 39
3.3.1
Linear classification
............................. 40
3.3.2
fc-nearest neighbor classification
...................... 40
3.3.3
Other supervised machine learning methods
................ 40
3.4
Review of terms
................................... 42
3.5
References
...................................... 43
4
The terminal is your friend
45
4.1
The Linux and Unix operating systems
....................... 46
4.1.1
Hold on
-
what is an operating system anyway?!
............. 46
4.2
The file system
................................... 47
4.2.1
Navigating the file system
.......................... 48
4.3
The terminal window
................................ 49
4.4
System utilities
................................... 50
4.4.1
Working with files
.............................. 50
4.4.2
Working with file content
.......................... 51
4.5
Review of terms
................................... 54
4.6
Computer exercise
.................................. 55
4.7
References
...................................... 58
5
/r[e-g]{2}ular expres+ions/
59
5.1
Pattern
........................................ 59
vi
5.2
A new language
................................... 60
5.2.1
The grammar
................................ 61
5.2.2
The vocabulary
............................... 61
5.2.3
Now what?
................................. 63
5.3
Computer exercise
.................................. 65
5.4
References
...................................... 67
6
R
69
6.1
Getting started
.................................... 69
6.2
Variables
....................................... 70
6.2.1
One-dimensional variables
.......................... 71
6.2.2
Multi-dimensional variables
......................... 72
6.3
Functions
...................................... 73
6.3.1
Mathematical functions
........................... 73
6.3.2
Vector functions
............................... 74
6.3.3
Other functions
............................... 75
6.4
Reading data into
R
................................. 75
6.5
Pretty pictures
.................................... 77
6.5.1
Generating graphics
............................. 77
6.5.2
Saving graphics
............................... 78
6.6
Computer exercise
.................................. 79
6.7
References
...................................... 84
II On your bioinformatics marks, ready
-
set
-
go!
85
7
The information superhighway
87
7.1
Online data
..................................... 87
7.2
Primary databases
.................................. 89
7.2.1
Sequences
.................................. 89
7.2.2
Structures
.................................. 94
7.3
Secondary databases
................................. 94
vii
7.3.1
Sequences
..................................
94
7.3.2
Structures
..................................
9б
7.3.3
Motifs, domains, families
.......................... 96
7.4
Controlled vocabularies
............................... 100
7.5
A final word of caution
...............................
Ю1
7.6
Review of terms
...................................
Ю2
7.7
Computer exercise: sequences
............................
ЮЗ
7.8
Computer exercise: structures
............................ 105
7.9
References
......................................
Ю7
8
Pairwise sequence comparisons
Ю9
8.1
What is an alignment, and what is it good for?
..................110
8.2
Dotplots
.......................................112
8.3
Evaluating alignments
................................113
8.3.1
Matrices for protein alignments
.......................115
8.3.2
Scoring schemes for
DNA
sequences
....................118
8.4
Computing pairwise alignments
...........................118
8.4.1
Optimal alignments
.............................118
8.4.2
Fast alignments
...............................120
8.5
Review of terms
...................................126
8.6
Computer exercise
..................................127
8.7
References
......................................129
9
Multiple sequence alignments
131
9.1
Evaluating multiple sequence alignments
...................... 132
9.1.1
Sum-of-pairs
................................. 132
9.1.2
Entropy
................................... 133
9.2
Computing multiple sequence alignments
...................... 134
9.2.1
Progressive sequence alignment
....................... 134
9.2.2
Iterative MSA approaches
.......................... 137
9.3
Final words
......................................
I37
viii
9.4
Computer
exercise
.................................. 138
9.5
References
...................................... 140
10
Trees
141
10.1
Anatomy of a phylogeny
.............................. 141
10.1.1
How many trees are there?
......................... 143
10.2
Computing phylogenies
............................... 144
10.2.1
Neighbor Joining
.............................. 144
10.2.2
Maximum parsimony
............................ 146
10.2.3
Maximum Likelihood
............................ 149
10.3
How confident are you?
............................... 149
10.4
Gene trees and species tree
............................. 151
10.5
Large scale phylogenetic analyses
.......................... 153
10.6
Review of terms
................................... 154
10.7
Computer exercise
.................................. 155
10.8
References
...................................... 157
11
Analysis and prediction of secondary structure
159
11.1
Assigning secondary structures in known protein structures
............ 159
11.1.1
DSSP
.................................... 160
11.2
Evaluation of predictions
.............................. 162
11.2.1
Q3 value
................................... 162
11.2.2
Matthews correlation coefficient
...................... 163
11.2.3
Segment overlap value
........................... 163
11.3
Predicting secondary structure from sequence
................... 164
11.3.1
First Generation approaches
........................ 165
11.3.2
Second generation approaches
....................... 166
11.3.3
Third generation approaches
........................ 167
11.4
Computer exercise
.................................. 169
11.5
References
...................................... 170
12
Comparison of
3D
structure
171
ix
-ι
70
12.1
Similar structures
..................................
LllL
12.2
Clique search
.....................................
175
12.3
Distance matrices
..................................
I77
12.4
Review of terms
...................................
179
12.5
Computer exercise
.................................. 18°
12.6
References
......................................
182
13
Prediction of
3D
structure 183
13.1
How does the biologist do it?
............................ 183
13.2
How does the physicist do it?
............................ 186
13.2.1
Energy functions
............................... 187
13.2.2
Energy minimization
-
molecular mechanics
................ 188
13.2.3
Molecular dynamics
............................. 188
13.3
When the biologist and the physicist finally meet
................. 188
13.4
References
...................................... 189
14
Statistically describing and displaying bioinformatics data
191
14.1
Just a sample
....................................192
14.2
Descriptive statistics
.................................193
14.2.1
Types of data
................................193
14.2.2
Number of variables
.............................194
14.2.3
Summarizing numerical data: univariate data
...............194
14.2.4
Summarizing categorical data: univariate data
...............199
14.2.5
Summarizing
Divariate data
.........................201
14.2.6
Summarizing multivariate data
.......................207
14.3
Inferential statistics
.................................207
14.3.1
Uncertainty
.................................208
14.3.2
Hypothesis testing
..............................208
14.4
Review of terms and concepts
....................... 209
14.5
Computer exercise
........................ 211
14.6
References
............................. 216
χ
15
Probability
217
15.1
Introduction to probability theory
.......................... 218
15.1.1
Trials, events, sample space
......................... 218
15.1.2
The nature of events
............................ 221
15.2
Probability distributions
............................... 223
15.2.1
Random variables
.............................. 223
15.2.2
Probability distributions
........................... 223
15.2.3
Common probability distributions (discrete)
................ 225
15.2.4
Common probability distributions (continuous)
.............. 230
15.3
Review of terms
................................... 233
15.4
Probability problems
................................. 234
15.5
Computer exercise
.................................. 235
15.6
References
...................................... 242
xi
|
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| author_facet | Hartmann, Stefanie Selbig, Joachim |
| author_role | aut aut |
| author_sort | Hartmann, Stefanie |
| author_variant | s h sh j s js |
| building | Verbundindex |
| bvnumber | BV035712112 |
| classification_rvk | WC 7700 |
| ctrlnum | (OCoLC)553762479 (DE-599)DNB996210903 |
| discipline | Biologie |
| format | Book |
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| illustrated | Illustrated |
| indexdate | 2024-07-09T21:51:43Z |
| institution | BVB |
| isbn | 9783837051896 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017989024 |
| oclc_num | 553762479 |
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| physical | XIV, 246 S. Ill., graph. Darst. 220 mm x 170 mm, 457 gr. |
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| publishDateSearch | 2009 |
| publishDateSort | 2009 |
| publisher | Books on Demand |
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| spelling | Hartmann, Stefanie Verfasser aut Introductory bioinformatics Stefanie Hartmann ; Joachim Selbig Norderstedt Books on Demand 2009 XIV, 246 S. Ill., graph. Darst. 220 mm x 170 mm, 457 gr. txt rdacontent n rdamedia nc rdacarrier Bioinformatik (DE-588)4611085-9 gnd rswk-swf (DE-588)4151278-9 Einführung gnd-content Bioinformatik (DE-588)4611085-9 s b DE-604 Selbig, Joachim Verfasser aut Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017989024&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Hartmann, Stefanie Selbig, Joachim Introductory bioinformatics Bioinformatik (DE-588)4611085-9 gnd |
| subject_GND | (DE-588)4611085-9 (DE-588)4151278-9 |
| title | Introductory bioinformatics |
| title_auth | Introductory bioinformatics |
| title_exact_search | Introductory bioinformatics |
| title_full | Introductory bioinformatics Stefanie Hartmann ; Joachim Selbig |
| title_fullStr | Introductory bioinformatics Stefanie Hartmann ; Joachim Selbig |
| title_full_unstemmed | Introductory bioinformatics Stefanie Hartmann ; Joachim Selbig |
| title_short | Introductory bioinformatics |
| title_sort | introductory bioinformatics |
| topic | Bioinformatik (DE-588)4611085-9 gnd |
| topic_facet | Bioinformatik Einführung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017989024&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT hartmannstefanie introductorybioinformatics AT selbigjoachim introductorybioinformatics |