Managing your biological data with python:
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Boca Raton, FL [u.a.]
CRC Press
2014
|
| Schriftenreihe: | Chapman & Hall/CRC mathematical and computational biology series
[52] |
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026998760&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XXV, 544 S. Ill., graph. Darst. |
| ISBN: | 9781439880937 143988093X |
Internformat
MARC
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Datensatz im Suchindex
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|---|---|
| adam_text | Chapman amp; Hall/CRC Mathematical and Computational Biology Series
Managing Your Biological
Data with Python
Ailegra Via
Kristian Rother
Anna Tramontano
CRC Press
Taylor amp; Francis Group
Boca Raton London New York
CRC Press is an imprint of the
Taylor amp; Francis Group, an informa business
ACHAPMAN amp;HALLBOOK
Table of Contents
Preface, xix
Acknowledgements, xxv
PART I Getting Started
CHAPTER 1 • The Python Shell 5
1 1 IN THIS CHAPTER YOU WILL LEARN 5
1 2 STORY: CALCULATING THE AG OF ATP HYDROLYSIS 5
121 Problem Description 5
122 Example Python Session 7
1 3 WHAT DO THE COMMANDS MEAN? 7
131 How to Run the Example on Your Computer 8
132 Variables 11
133 Importing Modules 14
134 Calculations 17
1 4 EXAMPLES 19
1 5 TESTING YOURSELF 21
CHAPTER 2 • Your First Python Program 23
2 1 IN THIS CHAPTER YOU WILL LEARN 23
2 2 STORY: HOW TO CALCULATE THE AMINO ACID
FREQUENCY IN THE SEQUENCE OF INSULIN 23
221 Problem Description 23
222 Example Python Session 26
viii • Table of Contents
2 3 WHAT DO THE COMMANDS MEAN? 26
231 How to Execute the Program 27
232 How Does the Program Work? 28
233 Comments 29
234 String Variables 30
235 Loops with for 33
236 Indentation 34
237 Printing to the Screen 35
2 4 EXAMPLES 37
2 5 TESTING YOURSELF 38
PART I Summary
PART II Data Management
CHAPTER 3 • Analyzing a Data Column 45
3 1 IN THIS CHAPTER YOU WILL LEARN 45
3 2 STORY: DENDRITIC LENGTHS 45
321 Problem Description 45
322 Example Python Session 46
3 3 WHAT DO THE COMMANDS MEAN? 47
331 Reading Text Files 47
332 Writing Text Files 48
333 Collecting Data in a List 50
334 Converting Text to Numbers 50
335 Converting Numbers to Text 51
336 Writing a Data Column to a Text File 52
337 Calculations on a List of Numbers 53
3 4 EXAMPLES 54
3 5 TESTING YOURSELF 57
CHAPTER 4 • Parsing Data Records 59
41^ IN THIS CHAPTER YOU WILL LEARN 59
Table of Contents • ix
4 2 STORY: INTEGRATING MASS SPECTROMETRY DATA
INTO METABOLIC PATHWAYS • 59
421 Problem Description 59
422 Example Python Session 61
4 3 WHAT DO THE COMMANDS MEAN? 61
431 The if/elif/else Statements 62
432 List Data Structures 65
43 3 Concise Ways to Create Lists 69
4 4 EXAMPLES 70
4 5 TESTING YOURSELF 75
CHAPTER 5 • Searching Data 77
5 1 IN THIS CHAPTER YOU WILL LEARN 77
5 2 STORY: TRANSLATING AN RNA SEQUENCE INTO
THE CORRESPONDING PROTEIN SEQUENCE 77
521 Problem Description 77
522 Example Python Session 78
5 3 WHAT DO THE COMMANDS MEAN? 80
531 Dictionaries 80
532 The while Statement 82
533 Searching with while Loops 84
534 Searching in a Dictionary 84
535 Searching in a List 85
5 4 EXAMPLES 86
5 5 TESTING YOURSELF 90
CHAPTER 6 • Filtering Data 93
6 1 IN THIS CHAPTER YOU WILL LEARN 93
6 2 STORY: WORKING WITH RNA-SEQ OUTPUT DATA 93
621 Problem Description 93
622 Example Python Session 96
6 3 WHAT DO THE COMMANDS MEAN? 97
631 Filtering with a Simple for if Combination 97
x • Table of Contents
632 Combining Two Data Sets 98
633 Differences between Two Data Sets 98
634 Removing from Lists, Dictionaries, and Files 99
635 Removing Duplicates Preserving and Not
Preserving Order 102
636 Sets 104
6 4 EXAMPLES 106
6 5 TESTING YOURSELF 108
CHAPTER 7 • Managing Tabular Data 111
7 1 IN THIS CHAPTER YOU WILL LEARN 111
7 2 STORY: DETERMINING PROTEIN CONCENTRATIONS 111
721 Problem Description 111
722 Example Python Session 113
7 3 WHAT DO THE COMMANDS MEAN? 114
731 Representing a Two-Dimensional Table 114
732 Accessing Rows and Single Cells 115
733 Inserting and Removing Rows 116
734 Accessing Columns 117
735 Inserting and Removing Columns 119
7 4 EXAMPLES 121
7 5 TESTING YOURSELF 127
CHAPTER 8 Sorting Data 129
•8 1 IN THIS CHAPTER YOU WILL LEARN 129
8 2 STORY: SORT A DATA TABLE 129
821 Problem Description 129
822 Example Python Session 130
8 3 WHAT DO THE COMMANDS MEAN? 130
831 Python Lists Are Good for Sorting 130
832 The sorted() Built-in Function 133
833 Sorting with itemgetter 133
834 Sorting in Ascending/Descending Order 134
Table of Contents • xi
835 Sorting Data Structures (Tuples, Dictionaries) 135
836 Sorting Strings by Their Length - 137
8 4 EXAMPLES 137
8 5 TESTING YOURSELF 141
CHAPTER 9 • Pattern Matching and Text Mining 143
9 1 IN THIS CHAPTER YOU WILL LEARN 143
9 2 STORY: SEARCH A PHOSPHORYLATION MOTIF IN A
PROTEIN SEQUENCE 143
921 Problem Description 143
922 Example Python Session 145
9 3 WHAT DO THE COMMANDS MEAN? 145
931 Compiling Regular Expressions 145
932 Pattern Matching 146
933 Grouping 148
934 Modifying Strings 150
9 4 EXAMPLES 154
9 5 TESTING YOURSELF 158
PART II Summary
PART III Modular Programming
CHAPTER 10 • Divide a Program into Functions 167
10 1 IN THIS CHAPTER YOU WILL LEARN 167
10 2 STORY: WORKING WITH THREE-DIMENSIONAL
COORDINATE FILES 167
10 2 1 Problem Description 167
10 2 2 Example Python Session 169
10 3 WHAT DO THE COMMANDS MEAN? 170
10 3 1 How to Define and Call Functions 172
10 3 2 Function Arguments 175
10 3 3 The struct Module 179
xii • Table of Contents
10 4 EXAMPLES 181
10 5 TESTING YOURSELF 185
CHAPTER 11 • Managing Complexity with Classes 189
11 1 IN THIS CHAPTER YOU WILL LEARN 189
11 2 STORY: MENDELIAN INHERITANCE 189
11 2 1 Problem Description 189
11 2 2 Example Python Session 190
11 3 WHAT DO THE COMMANDS MEAN? 191
11 3 1 Classes Are Used to Create Instances 192
11 3 2 Classes Contain Data in t he Form of Attributes 194
11 3 3 Classes Contain Methods 195
11 3 4 The repr Method Makes Classes
and Instances Printable 196
11 3 5 Using Classes Helps to Master
Complex Programs 197
11 4 EXAMPLES 199
11 5 TESTING YOURSELF 201
CHAPTER 12 • Debugging 205
12 1 IN THIS CHAPTER YOU WILL LEARN 205
12 2 STORY: WHEN YOUR PROGRAM DOES NOT WORK 205
12 2 1 Problem Description 205
12 2 2 Example Python Session 207
12 3 WHAT DO THE COMMANDS MEAN? 208
12 3 1 Syntax Errors 208
12 3 2 Runtime Errors 210
12 3 3 Handling Exceptions 213
12 3 4 When There Is No Error Message 215
12 4 EXAMPLES 219
12 5 TESTING YOURSELF 222
amp;
Table of Contents • xiii
CHAPTER 13 • Using External Modules: The Python
Interface to R 225
13 1 IN THIS CHAPTER YOU WILL LEARN 225
13 2 STORY: READING NUMBERS FROM A FILE AND
CALCULATING THEIR MEAN VALUE USING R WITH
PYTHON 225
13 2 1 Problem Description 225
13 2 2 Example Python Session 227
13 3 WHAT DO THE COMMANDS MEAN? 228
13 3 1 Therobjects Object of rpy2 and the r
Instance 228
13 3 2 Accessing an R Object from Python 228
13 3 3 Creating Vectors 230
13 3 4 Creating Matrices 231
13 3 5 Converting Python Objects into R Objects 234
13 3 6 How to Deal with Function Arguments That
Contain a Dot 235
13 4 EXAMPLES 236
13 5 TESTING YOURSELF 241
CHAPTER 14 • Building Program Pipelines 245
14 1 IN THIS CHAPTER YOU WILL LEARN 245
14 2 STORY: BUILDING AN NGS PIPELINE 245
14 2 1 Problem Description 245
14 2 2 Example Python Session 247
14 3 WHAT DO THE COMMANDS MEAN? 247
14 3 1 How to Use TopHat and Cu fflinks 249
14 3 2 What Is a Pipeline? 249
14 3 3 Exchanging Filenames and Data between Programs 251
14 3 4 Writing a Program Wrapper 252
14 3 5 Lag When Closing Files 253
14 3 6 Using Command-Line Parameters 254
xiv • Table of Contents
14 3 7 Testing Modules: if name ==
main 255
14 3 8 Working with Files and Directories 256
14 4 EXAMPLES 258
14 5 TESTING YOURSELF 260
CHAPTER 15 • Writing Good Programs 263
15 1 IN THIS CHAPTER YOU WILL LEARN 263
15 2 PROBLEM DESCRIPTION: UNCERTAINTY 263
15 2 1 There Is Uncertainty in Writing Programs 263
15 2 2 Example Programming Project 264
15 3 SOFTWARE ENGINEERING 265
15 3 1 Dividing a Programming Project into Smaller Tasks 265
15 3 2 Split a Program into Functions and Classes 267
15 3 3 Writing Well-Formatted Code 270
15 3 4 Using a Repository to Control Program Versions 271
15 3 5 How to Release Your Program to Other People 273
15 3 6 The Cycle of Software Development 275
15 4 EXAMPLE 278
15 5 TESTING YOURSELF 280
PART III Summary
PART IV Data Visualization
CHAPTER 16 Creating Scientific Diagrams 287
16 1 IN THIS CHAPTER YOU WILL LEARN 287
16 2 STORY: NUCLEOTIDE FREQUENCIES IN THE
RIBOSOME 287
16 2 1 Problem Description 288
16 2 2 Example Python Session 288
16 3 WHAT DO THE COMMANDS MEAN? 289
16 3 1 The matplotlib Library 289
Table of Contents • xv
16 3 2 Drawing Vertical Bars 290
16 3 3 Adding Labels to an x-Axis and y-Axis 291
16 3 4 Adding Tick Marks 291
16 3 5 Adding a Legend Box 292
16 3 6 Adding a Figure Title 292
16 3 7 Setting the Boundaries of the Diagram 292
16 3 8 Exporting an Image File in Low Resolution and
High Resolution 292
16 4 EXAMPLES 293
16 5 TESTING YOURSELF 298
CHAPTER 17 • Creating Molecule Images with PyMOL 301
17 1 IN THIS CHAPTER YOU WILL LEARN 301
17 2 STORY: THE ZINC FINGER 301
17 2 1 What Is PyMOL? 302
17 2 2 Example PyMOL Session 305
17 3 SEVEN STEPS TO CREATE A HIGH-RESOLUTION
IMAGE 306
17 3 1 Writing PyMOL Script Files 307
17 3 2 Loading and Saving Molecules 307
17 3 3 Selecting Parts of Molecules 309
17 3 4 Choose Representations for Each Selection 313
17 3 5 Setting Colors 315
17 3 6 Setting the Camera Position 316
17 3 7 Exporting a High-Resolution Image 317
17 4 EXAMPLES 319
17 5 TESTING YOURSELF 321
CHAPTER 18 • Manipulating Images 323
18 1 IN THIS CHAPTER YOU WILL LEARN 323
18 2 STORY: PLOT A PLASMID 323
18 2 1 Problem Description 324
18 2 2 Example Python Session 325
xvi • Table of Contents
18 3 WHAT DO THE COMMANDS MEAN? 326
18 3 1 Creating an Image 327
18 3 2 Reading and Writing Images 327
18 3 3 Coordinates 328
18 3 4 Drawing Geometrical Shapes 329
18 3 5 Rotating an Image 331
18 3 6 Adding Text Labels 331
18 3 7 Colors 332
18 3 8 Helper Variables 333
18 4 EXAMPLES 334
18 5 TESTING YOURSELF 336
PART IV Summary
PART V Biopython
CHAPTER 19 • Working with Sequence Data 347
19 1 IN THIS CHAPTER YOU WILL LEARN 347
19 2 STORY: HOW TO TRANSLATE A DNA CODING
SEQUENCE INTO THE CORRESPONDING PROTEIN
SEQUENCE AND WRITE IT TO A FASTA FILE 347
19 2 1 Problem Description 347
19 2 2 Example Python Session 348
19 3 WHAT DO THE COMMANDS MEAN? 348
19 3 1 The Seq Object 349
19 3 2 Working with Sequences as Strings 352
19 3 3 The MutableSeq Object 353
19 3 4 The SeqRecord Object 354
19 3 5 The SeqIO Module 356
19 4 EXAMPLES 358
19 5 TESTING YOURSELF 361
Table of Contents • xvii
CHAPTER 20 « Retrieving Data from Web Resources 363
20 1 IN THIS CHAPTER YOU WILL LEARN 363
20 2 STORY: SEARCHING PUBLICATIONS BY
KEYWORDS IN PUBMED AND DOWNLOADING
AND PARSING THE CORRESPONDING RECORDS 363
20 2 1 Problem Description 363
20 2 2 Python Session 364
20 3 WHAT DO THE COMMANDS MEAN? 365
20 3 1 The Entrez Module 365
20 3 2 The Medline Module 367
20 4 EXAMPLES 368
20 5 TESTING YOURSELF 372
CHAPTER 21 • Working with 3D Structure Data 375
21 1 IN THIS CHAPTER YOU WILL LEARN 375
21 2 STORY: EXTRACTING ATOM NAMES AND THREE-
DIMENSIONAL COORDINATES FROM A PDB FILE 375
21 2 1 Problem Description 376
21 2 2 Example Python Session 376
21 3 WHAT DO THE COMMANDS MEAN? 376
21 3 1 The Bio PDB Module 376
21 3 2 The SMCRA Object Hierarchy 378
21 4 EXAMPLES 384
21 5 TESTING YOURSELF 388
PART V Summary
PART VI Cookbook
Recipe 1 : The PyCogent Library 395
Recipe 2: Reversing and Randomizing a Sequence 399
Recipe 3: Creating a Random Sequence with Probabilities 403
Recipe 4: Parsing Multiple Sequence Alignments Using Biopython 405
xviii • Table of Contents
Recipe 5: Calculating a Consensus Sequence from a Multiple
Sequence Alignment 409
Recipe 6: Calculating the Distance between Phylogenetic
Tree Nodes 413
Recipe 7: Codon Frequencies in a Nucleotide Sequence 417
Recipe 8: Parsing RNA 2D Structures in the Vienna Format 421
Recipe 9: Parsing BLAST XML Output 425
Recipe 10: Parsing SBML Files 427
Recipe 11: Running BLAST 431
Recipe 12: Accessing, Downloading, and Reading Web Pages 437
Recipe 13: Parsing HTML Files 441
Recipe 14: Splitting a PDB File into PDB Chain Files 445
Recipe 15: Finding the Two Closest Ca Atoms in a PDB Structure 447
Recipe 16: Extracting the Interface between Two PDB Chains 451
Recipe 17: Building Homology Models Using Modeller 455
Recipe 18: RNA 3D Homology Modeling with ModeRNA 459
Recipe 19: Calculating RNA Base Pairs from a 3D Structure 463
Recipe 20: A Real Case of Structural Superimposition: The Serine
Protease Catalytic Triad 467
APPENDIX A: COMMAND OVERVIEW, 471
APPENDIX B: PYTHON RESOURCES, 495
APPENDIX C: RECORD SAMPLES, 499
APPENDIX D: HANDLING DIRECTORIES
AND PROGRAMS WITH UNIX, 507
INDEX, 525
|
| any_adam_object | 1 |
| author | Via, Allegra Rother, Kristian 1977- Tramontano, Andrea 1981- |
| author_GND | (DE-588)133397068 (DE-588)1022160656 |
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| bvnumber | BV041553059 |
| classification_rvk | WC 7700 |
| ctrlnum | (OCoLC)881534002 (DE-599)BVBBV041553059 |
| discipline | Biologie |
| format | Book |
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| id | DE-604.BV041553059 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T16:48:59Z |
| institution | BVB |
| isbn | 9781439880937 143988093X |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-026998760 |
| oclc_num | 881534002 |
| open_access_boolean | |
| owner | DE-20 DE-703 DE-29T |
| owner_facet | DE-20 DE-703 DE-29T |
| physical | XXV, 544 S. Ill., graph. Darst. |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| publisher | CRC Press |
| record_format | marc |
| series | Chapman & Hall/CRC mathematical and computational biology series |
| series2 | Chapman & Hall/CRC mathematical and computational biology series |
| spellingShingle | Via, Allegra Rother, Kristian 1977- Tramontano, Andrea 1981- Managing your biological data with python Chapman & Hall/CRC mathematical and computational biology series Bioinformatik (DE-588)4611085-9 gnd Python Programmiersprache (DE-588)4434275-5 gnd |
| subject_GND | (DE-588)4611085-9 (DE-588)4434275-5 |
| title | Managing your biological data with python |
| title_auth | Managing your biological data with python |
| title_exact_search | Managing your biological data with python |
| title_full | Managing your biological data with python Allegra Via ; Kristian Rother ; Anna Tramontano |
| title_fullStr | Managing your biological data with python Allegra Via ; Kristian Rother ; Anna Tramontano |
| title_full_unstemmed | Managing your biological data with python Allegra Via ; Kristian Rother ; Anna Tramontano |
| title_short | Managing your biological data with python |
| title_sort | managing your biological data with python |
| topic | Bioinformatik (DE-588)4611085-9 gnd Python Programmiersprache (DE-588)4434275-5 gnd |
| topic_facet | Bioinformatik Python Programmiersprache |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026998760&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV021728115 |
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