The analysis of gene expression data: methods and software
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
New York, NY [u.a.]
Springer
2003
|
| Schriftenreihe: | Statistics for biology and health
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Literaturangaben |
| Beschreibung: | XIX, 455 S. Ill., graph. Darst. : 24 cm |
| ISBN: | 0387955771 |
Internformat
MARC
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| 245 | 1 | 0 | |a The analysis of gene expression data |b methods and software |c Giovanni Parmigiani ... ed. |
| 264 | 1 | |a New York, NY [u.a.] |b Springer |c 2003 | |
| 300 | |a XIX, 455 S. |b Ill., graph. Darst. : 24 cm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Statistics for biology and health | |
| 500 | |a Literaturangaben | ||
| 650 | 7 | |a Gene Expression |2 cabt | |
| 650 | 7 | |a Data Analysis |2 cabt | |
| 650 | 7 | |a Computer Software |2 cabt | |
| 650 | 4 | |a Expression génique - Informatique | |
| 650 | 4 | |a Expression génique - Recherche - Méthodologie | |
| 650 | 4 | |a Puces à ADN | |
| 650 | 4 | |a Datenverarbeitung | |
| 650 | 4 | |a DNA microarrays | |
| 650 | 4 | |a Data Interpretation, Statistical | |
| 650 | 4 | |a Gene Expression Profiling |x methods | |
| 650 | 4 | |a Gene expression |x Data processing | |
| 650 | 4 | |a Gene expression |x Research |x Methodology | |
| 650 | 4 | |a Oligonucleotide Array Sequence Analysis |x methods | |
| 650 | 0 | 7 | |a Datenanalyse |0 (DE-588)4123037-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Microarray |0 (DE-588)4544227-7 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Genexpression |0 (DE-588)4020136-3 |2 gnd |9 rswk-swf |
| 655 | 7 | |0 (DE-588)4143413-4 |a Aufsatzsammlung |2 gnd-content | |
| 689 | 0 | 0 | |a Genexpression |0 (DE-588)4020136-3 |D s |
| 689 | 0 | 1 | |a Microarray |0 (DE-588)4544227-7 |D s |
| 689 | 0 | 2 | |a Datenanalyse |0 (DE-588)4123037-1 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Parmigiani, Giovanni |e Sonstige |0 (DE-588)124676952 |4 oth | |
| 856 | 4 | 2 | |m HBZ Datenaustausch |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010376682&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
Datensatz im Suchindex
| _version_ | 1805078948391944192 |
|---|---|
| adam_text |
Contents
Preface v
Contributors xvii
Color Insert (facing page 236)
1 The Analysis of Gene Expression Data: An Overview of
Methods and Software 1
Giovanni Parmigiani, Elizabeth S. Garrett, Rafael A. Irizarry,
and Scott L. Zeger
1.1 Measuring Gene Expression Using Microarrays 1
1.1.1 Microarray Technologies 1
1.1.2 Sources of Variation in Gene Expression
Measurements Using Microarrays 4
1.1.3 Phases of Microarray Data Analysis 5
1.2 Design of Microarray Experiments 7
1.2.1 Replication and Sample Size Considerations . 7
1.2.2 Design of Two Channel Arrays 9
1.3 Data Storage 9
1.3.1 Databases 9
1.3.2 Standards 10
1.3.3 Statistical Analysis Languages 11
1.4 Preprocessing 12
1.4.1 Image Analysis 12
1.4.2 Visualizations for Quality Control 12
1.4.3 Background Subtraction 13
1.4.4 Probe level Analysis of Oligonucleotide Arrays . 14
1.4.5 Within Array Normalization of cDNA Arrays . . 15
1.4.6 Normalization Across Arrays 15
1.5 Screening for Differentially Expressed Genes 16
1.5.1 Estimation or Selection? 16
1.5.2 One Problem or Many? 17
1.5.3 Selection and False Discovery Rates 18
1.5.4 Beyond Two Groups 19
1.6 Challenges of Genome Biometry Analyses 19
vii
viii Contents
1.7 Visualization and Unsupervised Analyses 21
1.7.1 Profile Visualization 21
1.7.2 Why Clustering? 22
1.7.3 Hierarchical Clustering 23
1.7.4 fc Means Clustering and Self Organizing Maps . 25
1.7.5 Model Based Clustering 26
1.7.6 Principal Components Analysis 26
1.7.7 Multidimensional Scaling 27
1.7.8 Identifying Novel Molecular Subclasses 27
1.7.9 Time Series Analysis 28
1.8 Prediction 29
1.8.1 Prediction Tools 29
1.8.2 Dimension Reduction 30
1.8.3 Evaluation of Classifiers 30
1.8.4 Regression Based Approaches 31
1.8.5 Classification Trees 31
1.8.6 Probabilistic Model Based Classification 32
1.8.7 Discriminant Analysis 33
1.8.8 Nearest Neighbor Classifiers 33
1.8.9 Support Vector Machines 33
1.9 Free and Open Source Software 33
1.9.1 Whitehead Institute Tools 34
1.9.2 Eisen Lab Tools 34
1.9.3 TIGR Tools 34
1.9.4 GeneX and CyberT 35
1.9.5 Projects at NCBI 35
1.9.6 BRB 35
1.9.7 The OOML library 36
1.9.8 MatArray 36
1.9.9 BASE 36
1.10 Conclusion 36
2 Visualization and Annotation of
Genomic Experiments 46
Robert Gentleman and Vincent Carey
2.1 Introduction 46
2.2 Motivations for Component Based Software 47
2.3 Formalism 49
2.4 Bioconductor Software for Filtering, Exploring, and
Interpreting Microarray Experiments 50
2.4.1 Formal Data Structures and Methods for
Multiple Microarrays 50
2.4.2 Tools for Filtering Gene Expression Data:
The Closure Concept 54
Contents ix
2.4.3 Expression Density Diagnostics:
High Throughput Exploratory Data
Analysis for Microarrays 55
2.4.4 Annotation 57
2.5 Visualization 58
2.5.1 Chromosomes 59
2.6 Applications 64
2.6.1 A Case Study of Gene Filtering 64
2.6.2 Application of Expression Density Diagnostics . 67
2.7 Conclusions 70
3 Bioconductor R Packages for Exploratory Analysis
and Normalization of cDNA Microarray Data 73
Sandrine Dudoit and Jean Fee Hwa Yang
3.1 Introduction 73
3.1.1 Overview of Packages 73
3.1.2 Two Color cDNA Microarray Experiments . 75
3.2 Methods 76
3.2.1 Standards for Microarray Data 76
3.2.2 Object Oriented Programming: Microarray
Classes and Methods 77
3.2.3 Diagnostic Plots 78
3.2.4 Normalization Using Robust Local Regression . 79
3.3 Application: Swirl Microarray Experiment 80
3.4 Software 81
3.4.1 Package marrayClasses—Classes and Methods
for cDNA Microarray Data 81
3.4.2 Package marrayInput—Data Input for cDNA
Microarrays 89
3.4.3 Package marrayPlots—Diagnostic Plots for
cDNA Microarray Data 91
3.4.4 Package marrayNonn—Location and Scale
Normalization for cDNA Microarray Data . 96
3.5 Discussion 99
4 An R Package for Analyses of Affymetrix
Oligonucleotide Arrays 102
Rafael A. Irizarry, Laurent Gautier, and Leslie M. Cope
4.1 Introduction 102
4.2 Methods 103
4.2.1 Notation 103
4.2.2 The CEL/CDF Convention 104
4.2.3 Probe Pair Sets 106
4.2.4 Probe Level Objects 107
x Contents
4.2.5 Normalization 108
4.2.6 Exploratory Data Analysis of
Probe Level Data Ill
4.3 Application 113
4.3.1 Expression Measures 113
4.4 Software 115
4.4.1 A Case Study 115
4.4.2 Extending the Package 118
4.5 Conclusion 118
5 DNA Chip Analyzer (dChip) 120
Cheng Li and Wing Hung Wong
5.1 Introduction 120
5.2 Methods 121
5.2.1 Normalization of Arrays Based on an
"Invariant Set" 121
5.2.2 Model Based Analysis of
Oligonucleotide Arrays 122
5.2.3 Confidence Interval for Fold Change 122
5.2.4 Pooling Replicate Arrays Considering
Measurement Accuracy 124
5.3 Software and Applications 125
5.3.1 Reading in Array Data Files 125
5.3.2 Viewing an Array Image 127
5.3.3 Normalizing Arrays 129
5.3.4 Viewing PM/MM Data 129
5.3.5 Calculating Model Based Expression Indexes . . 131
5.3.6 Filter Genes 132
5.3.7 Hierarchical Clustering 133
5.3.8 Comparing Samples 135
5.3.9 Mapping Genes to Chromosomes 137
5.3.10 Sample Classification by Linear
Discriminant Analysis 138
5.4 Discussion 139
6 Expression Profiler 142
Jaak Vilo, Misha Kapushesky, Patrick Kemmeren, Ugis Sarkans,
and Alvis Brazma
6.1 Introduction 142
6.2 EPCLUST 143
6.2.1 EPCLUST: Data Import 143
6.2.2 EPCLUST: Data Filtering 144
6.2.3 EPCLUST: Data Annotation 146
6.2.4 EPCLUST: Data Environment 147
Contents xi
6.2.5 EPCLUST: Data Analysis 148
6.3 URLMAP: Cross Linking of the Analysis Results
Between the Tools and Databases 151
6.4 EP:GO GeneOntology Browser 152
6.5 EP:PPI: Comparison of Protein Pairs and Expression . . 153
6.6 Pattern Discovery, Pattern Matching, and
Visualization Tools 154
6.7 An Example of the Data Analysis and Visualizations
Performed by the Tools in Expression Profiler 154
6.8 Integration of Expression Profiler with Public
Microarray Databases 159
6.9 Conclusions 160
7 An S PLUS Library for the Analysis and Visualization
of Differential Expression 163
Jae K. Lee and Michael O'Connell
7.1 Introduction 163
7.2 Assessment of Differential Expression 164
7.2.1 Local Pooled Error 165
7.2.2 Tests for Differential Expression 169
7.2.3 Cluster Analysis and Visualization 171
7.3 Analysis of Melanoma Expression 174
7.3.1 Tests for Differential Expression 175
7.3.2 Cluster Analysis and Visualization 178
7.3.3 Annotation 180
7.4 Discussion 181
8 DRAGON and DRAGON View: Methods for the
Annotation, Analysis, and Visualization of Large Scale
Gene Expression Data 185
Christopher M.L.S. Bouton, George Henry, Carlo Colantuoni,
and Jonathan Pevsner
8.1 Introduction 185
8.2 System and Methods 189
8.2.1 Overview of DRAGON 189
8.2.2 DRAGON's Hardware, Software, and
Database Architecture 190
8.2.3 Cross Referencing Information in DRAGON . . 192
8.2.4 The DRAGON Search and Annotate Tools . 193
8.2.5 The DRAGON View Data Visualization Tools . 196
8.2.6 DRAGON Gram: A Novel Visualization Tool . . 198
8.3 Implementation 199
8.4 Discussion and Conclusion 204
xii Contents
9 SNOMAD: Biologist Friendly Web Tools
for the Standardization and Normalization
of Microarray Data 210
Carlo Colantuoni, George Henry, Christopher M.L.S. Bouton,
Scott L. Zeger, and Jonathan Pevsner
9.1 Introduction 210
9.2 Methods and Application 212
9.2.1 Overview of Experimental and Data
Analysis Procedures 212
9.2.2 Background Subtraction 214
9.2.3 Global Mean Normalization 214
9.2.4 Standard Data Transformation and
Visualization Methods 215
9.2.5 Local Mean Normalization Across Element
Signal Intensity 217
9.2.6 Local Variance Correction Across Element
Signal Intensity 219
9.2.7 Local Mean Normalization Across the
Microarray Surface 223
9.3 Software 225
9.4 Discussion 226
10 Microarray Analysis Using the MicroArray Explorer 229
Peter F. Lemkin, Gregory C. Thornwall, and Jai Evans
10.1 Introduction 2J9
10.1.1 Need for the Methodology 230
10.1.2 Basic Ideas Behind the Approach 231
10.2 Methods—Statistical and Informatics Basis 232
10.2.1 Analysis Paradigm 235
10.2.2 Particular Analysis Methods 238
10.2.3 Data Conversion 238
10.3 Software 239
10.3.1 System Design—Software Implementation . 244
10.3.2 How to Download the Software 247
10.3.3 Strengths and Weaknesses of the Approach . . . 248
10.4 Applications 249
10.5 Discussion 251
11 Parametric Empirical Bayes Methods for Microarrays 254
Michael A. Newton and Christina Kendziorski
11.1 Introduction 254
11.2 EB Methods 256
11.2.1 Canonical EB Example 256
11.2.2 General Model Structure: Two Conditions . 256
Contents xiii
11.2.3 Multiple Conditions 258
11.2.4 The Gamma Gamma and
Lognormal Normal Models 259
11.2.5 Model Fitting 260
11.3 Software 261
11.4 Application 263
11.5 Discussion 269
12 SAM Thresholding and False Discovery Rates
for Detecting Differential Gene Expression
in DNA Microarrays 272
John D. Storey and Robert Tibshirani
12.1 Introduction 272
12.2 Methods and Applications 273
12.2.1 Multiple Hypothesis Testing 273
12.2.2 An Application 275
12.2.3 Forming the Test Statistics 276
12.2.4 Calculating the Null Distribution 277
12.2.5 The SAM Thresholding Procedure 278
12.2.6 Estimating False Discovery Rates 280
12.3 Software 283
12.3.1 Obtaining the Software 283
12.3.2 Data Formats 283
12.3.3 Response Format 284
12.3.4 Example Input Data File for an
Unpaired Problem 285
12.3.5 Block Permutations 285
12.3.6 Normalization of Experiments 285
12.3.7 Handling Missing Data 287
12.3.8 Running SAM 287
12.3.9 Format of the Significant Gene List 288
12.4 Discussion 289
13 Adaptive Gene Picking with Microarray Data:
Detecting Important Low Abundance Signals 291
Yi Lin, Samuel T. Nadler, Hong Lan, Alan D. Attie,
and Brian S. Yandell
13.1 Introduction 291
13.2 Methods 292
13.2.1 Background Subtraction 292
13.2.2 Transformation to Approximate Normality . . . 293
13.2.3 Differential Expression Across Conditions . 295
13.2.4 Robust Center and Spread 297
xiv Contents
13.2.5 Formal Evaluation of Significant
Differential Expression 299
13.2.6 Simulation Studies 301
13.2.7 Comparison of Methods with E. coli Data . 304
13.3 Software 304
13.4 Application 306
13.4.1 Diabetes and Obesity Studies 306
13.4.2 Software Example 308
14 MAANOVA: A Software Package for the Analysis of
Spotted cDNA Microarray Experiments 313
Hao Wu, M. Kathleen Kerr, Xiangqin Cui,
and Gary A. Churchill
14.1 Introduction 313
14.2 Methods 314
14.2.1 Data Acquisition 315
14.2.2 ANOVA Models for Microarray Data 315
14.2.3 Experimental Design for Microarrays 317
14.2.4 Data Transformations 321
14.2.5 Algorithms for Computing ANOVA Estimates . 322
14.2.6 Statistical Inference 323
14.2.7 Cluster Analysis 327
14.3 Software 328
14.3.1 Availability 328
14.3.2 Functionality 329
14.4 Data Analysis with MAANOVA 334
14.5 Discussion 339
15 GeneClust 342
Kim Anh Do, Bradley Broom, and Sijin Wen
15.1 Introduction 342
15.2 Methods 343
15.2.1 Algorithm 343
15.2.2 Choice of Cluster Size via the Gap Statistic . . . 344
15.2.3 Supervised Gene Shaving for
Class Discrimination 346
15.3 Software 347
15.3.1 The GeneShaving Package 347
15.3.2 GeneClust: A Faster Implementation of
Gene Shaving 352
15.4 Applications 354
15.4.1 The Alon Colon Dataset 354
15.4.2 The NCI60 Dataset 356
15.5 Discussion 358
Contents xv
16 POE: Statistical Methods for Qualitative Analysis of
Gene Expression 362
Elizabeth S. Garrett and Giovanni Parmigiani
16.1 Introduction 362
16.2 Methodology 364
16.2.1 Mixture Model for Gene Expression 364
16.2.2 Useful Representations of the Results 366
16.2.3 Bayesian Hierarchical Model Formulation . 367
16.2.4 Restrictions to Remove Ambiguity in the
Case of Only Two Components 368
16.2.5 Mining for Subsets of Genes 368
16.2.6 Creating Molecular Profiles 370
16.3 R Software Extension: POE 371
16.3.1 An Example of Using POE on
Simulated Data 371
16.3.2 Estimating Posterior Probability of
Expression Using poe. fit 372
16.3.3 Visualization Tools 374
16.3.4 Gene Mining Functions 377
16.3.5 Molecular Profiling Tool 379
16.4 Results of POE Applied to Lung Cancer Data 381
16.5 Discussion and Future Work 384
17 Bayesian Decomposition 388
Michael F. Ochs
17.1 Introduction 388
17.1.1 Role of Signaling and Metabolic Pathways . 388
17.1.2 Gene Expression Microarrays 389
17.2 Methods 390
17.2.1 Matrix Decomposition 390
17.2.2 Markov Chain Monte Carlo 391
17.2.3 Bayesian Framework 392
17.2.4 The Prior Distribution 393
17.2.5 Summary Statistics 395
17.3 Software 396
17.3.1 Implementation 396
17.3.2 Files and Installation 396
17.3.3 Issues in the Application of
Bayesian Decomposition 397
17.4 Application of Bayesian Decomposition to Yeast
Cell Cycle Data 398
17.4.1 Preparation of the Data 398
17.4.2 Running the Program 399
17.4.3 Visualizing the Output 400
xvi Contents
17.4.4 Interpretation 402
17.4.5 Advantages of Bayesian Decomposition 403
17.5 Discussion 403
18 Bayesian Clustering of Gene Expression Dynamics 409
Paola Sebastiani, Marco Ramoni, and Isaac S. Kohane
18.1 Introduction 409
18.2 Methods 411
18.2.1 Modeling Time 412
18.2.2 Probabilistic Scoring Metric 413
18.2.3 Heuristic Search 415
18.2.4 Statistical Diagnostics 416
18.3 Software 417
18.3.1 Screen 0: Welcome Screen 417
18.3.2 Screen 1: Getting Started 418
18.3.3 Screen 2: Analysis 418
18.3.4 Screen 3: Cluster Model 419
18.3.5 Screen 4: Pack and Go! 419
18.4 Application 420
18.4.1 Analysis 420
18.4.2 Statistical Diagnostics 421
18.4.3 Understanding the Model 421
18.5 Conclusions 424
19 Relevance Networks: A First Step Toward
Finding Genetic Regulatory Networks Within
Microarray Data 428
Atul J. Butte and Isaac S. Kohane
19.1 Introduction 428
19.1.1 Advantages of Relevance Networks 429
19.2 Methodology 431
19.2.1 Formal Definition of Relevance Networks . 431
19.2.2 Finding Regulatory Networks in
Phenotypic Data 432
19.2.3 Using Entropy and Mutual Information to
Evaluate Gene Gene Associations 434
19.3 Applications 437
19.3.1 Finding Pharmacogenomic
Regulatory Networks 437
19.3.2 Setting the Threshold 439
19.4 Software 440
Index 447 |
| any_adam_object | 1 |
| author_GND | (DE-588)124676952 |
| building | Verbundindex |
| bvnumber | BV017219483 |
| callnumber-first | Q - Science |
| callnumber-label | QP624 |
| callnumber-raw | QP624.5.D726 |
| callnumber-search | QP624.5.D726 |
| callnumber-sort | QP 3624.5 D726 |
| callnumber-subject | QP - Physiology |
| classification_rvk | QH 252 WC 4460 WC 7000 WG 1750 ZA 62000 |
| classification_tum | BIO 180f BIO 110f |
| ctrlnum | (OCoLC)612180763 (DE-599)BVBBV017219483 |
| dewey-full | 572.8/65 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 572 - Biochemistry |
| dewey-raw | 572.8/65 |
| dewey-search | 572.8/65 |
| dewey-sort | 3572.8 265 |
| dewey-tens | 570 - Biology |
| discipline | Biologie Informatik Agrar-/Forst-/Ernährungs-/Haushaltswissenschaft / Gartenbau Wirtschaftswissenschaften |
| format | Book |
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| genre_facet | Aufsatzsammlung |
| id | DE-604.BV017219483 |
| illustrated | Illustrated |
| indexdate | 2024-07-20T06:37:11Z |
| institution | BVB |
| isbn | 0387955771 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-010376682 |
| oclc_num | 612180763 |
| open_access_boolean | |
| owner | DE-355 DE-BY-UBR DE-739 DE-91G DE-BY-TUM DE-M49 DE-BY-TUM DE-703 DE-19 DE-BY-UBM DE-11 DE-188 DE-578 |
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| physical | XIX, 455 S. Ill., graph. Darst. : 24 cm |
| publishDate | 2003 |
| publishDateSearch | 2003 |
| publishDateSort | 2003 |
| publisher | Springer |
| record_format | marc |
| series2 | Statistics for biology and health |
| spelling | The analysis of gene expression data methods and software Giovanni Parmigiani ... ed. New York, NY [u.a.] Springer 2003 XIX, 455 S. Ill., graph. Darst. : 24 cm txt rdacontent n rdamedia nc rdacarrier Statistics for biology and health Literaturangaben Gene Expression cabt Data Analysis cabt Computer Software cabt Expression génique - Informatique Expression génique - Recherche - Méthodologie Puces à ADN Datenverarbeitung DNA microarrays Data Interpretation, Statistical Gene Expression Profiling methods Gene expression Data processing Gene expression Research Methodology Oligonucleotide Array Sequence Analysis methods Datenanalyse (DE-588)4123037-1 gnd rswk-swf Microarray (DE-588)4544227-7 gnd rswk-swf Genexpression (DE-588)4020136-3 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Genexpression (DE-588)4020136-3 s Microarray (DE-588)4544227-7 s Datenanalyse (DE-588)4123037-1 s DE-604 Parmigiani, Giovanni Sonstige (DE-588)124676952 oth HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010376682&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | The analysis of gene expression data methods and software Gene Expression cabt Data Analysis cabt Computer Software cabt Expression génique - Informatique Expression génique - Recherche - Méthodologie Puces à ADN Datenverarbeitung DNA microarrays Data Interpretation, Statistical Gene Expression Profiling methods Gene expression Data processing Gene expression Research Methodology Oligonucleotide Array Sequence Analysis methods Datenanalyse (DE-588)4123037-1 gnd Microarray (DE-588)4544227-7 gnd Genexpression (DE-588)4020136-3 gnd |
| subject_GND | (DE-588)4123037-1 (DE-588)4544227-7 (DE-588)4020136-3 (DE-588)4143413-4 |
| title | The analysis of gene expression data methods and software |
| title_auth | The analysis of gene expression data methods and software |
| title_exact_search | The analysis of gene expression data methods and software |
| title_full | The analysis of gene expression data methods and software Giovanni Parmigiani ... ed. |
| title_fullStr | The analysis of gene expression data methods and software Giovanni Parmigiani ... ed. |
| title_full_unstemmed | The analysis of gene expression data methods and software Giovanni Parmigiani ... ed. |
| title_short | The analysis of gene expression data |
| title_sort | the analysis of gene expression data methods and software |
| title_sub | methods and software |
| topic | Gene Expression cabt Data Analysis cabt Computer Software cabt Expression génique - Informatique Expression génique - Recherche - Méthodologie Puces à ADN Datenverarbeitung DNA microarrays Data Interpretation, Statistical Gene Expression Profiling methods Gene expression Data processing Gene expression Research Methodology Oligonucleotide Array Sequence Analysis methods Datenanalyse (DE-588)4123037-1 gnd Microarray (DE-588)4544227-7 gnd Genexpression (DE-588)4020136-3 gnd |
| topic_facet | Gene Expression Data Analysis Computer Software Expression génique - Informatique Expression génique - Recherche - Méthodologie Puces à ADN Datenverarbeitung DNA microarrays Data Interpretation, Statistical Gene Expression Profiling methods Gene expression Data processing Gene expression Research Methodology Oligonucleotide Array Sequence Analysis methods Datenanalyse Microarray Genexpression Aufsatzsammlung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010376682&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT parmigianigiovanni theanalysisofgeneexpressiondatamethodsandsoftware |