Computing for biologists:
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2014
|
| Ausgabe: | 1. publ. |
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027566933&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027566933&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| Beschreibung: | Includes index |
| Umfang: | X, 207 S. |
| ISBN: | 9781107042827 9781107642188 |
Internformat
MARC
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Datensatz im Suchindex
| _version_ | 1819348906070245376 |
|---|---|
| adam_text | CONTENTS
Preface page
ix
0
Meet Python
1
0.1
Getting Started
1
0.2
Big Numbers
3
0.3
Strange Division
3
0.4
Naming Things
4
0.5
What s in a Name?
6
0.6
From Numbers to Strings.
.. 6
0.7
Slicing
8
0.8
Adding Strings
9
0.9
Negative Indices
10
0.10
Fancy Slicing
10
0.11
And Now to Lists.
.. 11
0.12
Lists for Free!
13
0.13
Changing Values
14
0.14
More on Mutability
17
0.15
Booleans
18
Putting it All Together
21
Part I Python versus Pathogens
23
1
Computing GC Content
25
1.1
Representing
DNA
on a Computer
26
1.2
Python Functions
26
1.3
A Short Comment on Docstrings
28
1.4
Bigger and Better Functions
28
1.5
Why Write Functions?
29
1.6
Making Decisions
29
1.7
A Potential Pitfall
32
1.8
GC Content of Strings of Length
1, 2, 3,
or
4:
if, elif
,
else
34
1.9
Oops!
36
1.10
The Perfect GC Content
Funăion:
for Loops
38
CONTENTS
1.11
Another Example of for Loops: Converting
DNA
to
RNA
39
Putting it All Together
40
2
Pathogenicity Islands
41
2.1
How Salmonella Enters Host Cells
41
2.2
Investigating Pathogenicity Islands
43
2.3
Looping Over Lists
44
2.4
Looping Over Lists with range
45
2.5
From Gum to CAT Boxes
47
2.6
Functions Can Call Other Functions!
49
Putting it All Together
52
3
Open Reading Frames and Genes
53
3.1
Open Reading Frames and the Central Dogma
53
3.2
GC Content and ORFs
54
3.3
The count Start
s
Function
56
3.4
The
genst
ring Function
57
3.5
while Loops and Population Genetics
59
Putting it All Together
64
4
Finding Genes (at last!)
65
4.1
From ORFs to Genes
65
4.2
Genes Occur on Both Strands
67
4.3
Determining the Function of a Protein
67
Putting it
Ali
Together
69
Part II Sequence Alignment and Sex Determination
71
5
Recursion
75
5.1
A Brief Diversion Before Recursion
76
5.2
And Now For Recursion!
77
5.3
The Factorial Function
80
5.4
How to Write a Recursive Function
82
5.5
Another Example: Recursive Reverse
85
Putting it All Together
85
6
The Use-lt-Or-Lose-lt Principle
87
6.1
Peptide
Fragments
87
6.2
Making Change
92
CONTENTS
6.3
Longest Common Subsequence
96
Putting it All Together
99
7
Dictionaries, Memoization, and Speed
100
7.1
Dictionaries
101
7.2
Using a Dictionary
102
7.3
What Kinds of Things Can be Keys and Values?
103
7.4
Optional Section: How Dictionaries Work (and why you should care)
105
7.5
Memoization
109
7.6
Memoizing LCS
113
Putting it All Together
115
8
Sequence Alignment and the Evolution of Sex Chromosomes
116
8.1
The Sequence Alignment Score
116
8.2
From Scores to Alignments
121
8.3
Sequence Alignment Scoring with Variable Rewards and Penalties
123
8.4
Optional Section: How Substitution Matrices are Computed
126
8.5
Optional Section: Getting the Actual Sequence Alignment
129
8.6
Identifying Orthologs
135
8.7
Comparing Chromosomes
136
Putting it All Together
138
Part III Phlyogenetic Reconstruction and the Origin
of Modern Humans
141
9
Representing and Working with Trees
145
9.1
Representing Trees
146
9.2
Computing with Trees
148
Putting it All Together
152
10
Drawing Trees
154
10.1
Drawing Fractal Trees
158
10.2
Drawing Phylogenetic Trees
159
Putting it All Together
162
11
The UPGMA Algorithm
163
11.1
The Algorithm
164
11.2
Implementing UPGMA in Python
169
11.3
Calibrating Trees
171
Putting it All Together
172
CONTENTS
Part IV Additional Topics
175
12
RNA
Secondary Structure Prediction
177
13
Gene Regulatory Networks and the Maximum
Likelihood Method
186
Putting it All Together
195
14
Birds, Bees, and Genetic Algorithms
196
14.1
Fast Algorithms
198
14.2
Slow Algorithms
199
14.3
Genetic Algorithms
201
Where to go from here
205
Index
206
In my
20
years as a professor, I have never run across a textbook on
bioinformatics algorithms that a biologist can read from cover to cover
and understand.This is the one.
Pavel Pevzner, Ronald R. Taylor Distinguished Professor of Computer
Science, University of California at San Diego
Don t have a computing background, but need to learn how to solve
real biological problems using computational tools? Need to improve
your confidence in programming for biological applications?
Specifically designed for undergraduate students in the life sciences with no previous
programming experience, this textbook addresses both of these needs and more.
•
Teaches general and widely-applicable Python programming skills, applicable to
both Python versions
2
and
3
•
Each major part poses a compelling biological question before providing the
algorithmic ideas and programming tools necessary to explore it
-
algorithms
covered include gene finding, sequence alignment, and phylogenetic methods
•
Explains the design of efficient algorithms, simulation, NP-hardness, and the
maximum likelihood method, among other key concepts and methods
•
Designed to equip students with the skills to write programs for solving a range of
biological problems, the book is accompanied by numerous prograrmning exercises
available at www.cs.hmc.edu/CFB
|
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| id | DE-604.BV042126745 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T17:02:57Z |
| institution | BVB |
| isbn | 9781107042827 9781107642188 |
| language | English |
| lccn | 2014014322 |
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| spellingShingle | Libeskind-Hadas, Ran Bush, Eliot Computing for biologists Python Programmiersprache (DE-588)4434275-5 gnd Biologie (DE-588)4006851-1 gnd |
| subject_GND | (DE-588)4434275-5 (DE-588)4006851-1 |
| title | Computing for biologists |
| title_auth | Computing for biologists |
| title_exact_search | Computing for biologists |
| title_full | Computing for biologists Ran Libeskind-Hadas ; Eliot Bush |
| title_fullStr | Computing for biologists Ran Libeskind-Hadas ; Eliot Bush |
| title_full_unstemmed | Computing for biologists Ran Libeskind-Hadas ; Eliot Bush |
| title_short | Computing for biologists |
| title_sort | computing for biologists |
| topic | Python Programmiersprache (DE-588)4434275-5 gnd Biologie (DE-588)4006851-1 gnd |
| topic_facet | Python Programmiersprache Biologie |
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