The digital cell cell biology as a data science
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cold Spring Harbor, New York
Cold Spring Harbor Laboratory Press
[2020]
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| Online-Zugang: | Inhaltsverzeichnis |
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| 245 | 1 | 0 | |a The digital cell |b cell biology as a data science |c Stephen J. Royle, University of Warwick |
| 264 | 1 | |a Cold Spring Harbor, New York |b Cold Spring Harbor Laboratory Press |c [2020] | |
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Datensatz im Suchindex
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| adam_text | Contents Preface xi Acknowledgments xiii 1. The Digital Cell Philosophy 1 Workflows and Pipelines Using Spreadsheets for Experimental Data Software for Digital Cell Biology Focusing on Imaging Golden Rules 2. Dealing with Data 1 2 4 4 4 7 Why Is Organization So Important? Getting Organized 7 8 8 11 12 13 18 18 I7 Experiment-Based Organization Databases for Resources Electronic Lab Notebooks (ELNs) Databases for Imaging Data Sharing Your Data Externally Backing Up Your Data Golden Rules 3. Imaging Data Software Selection 19 20 20 21 24 24 23 22 29 Fiji RStudio What Is an Image? /mage Formats Image Types Multidimensional Image Files Metadata Image Transformation vii
viii Contents Imaging Information Trade-Offs in Imaging Focus and Dealing with Drift Phototoxicity and Photobleaching Choice of Fluorophores Dynamic Range Golden Rules 4. Image Processing and Analysis How to Analyze an Image Tutorial: Quantifying Cell Protein Levels from Immunofluorescence Images Segmentation Further Segmentation Approaches Image Filters Cel Densitometry Tutorial: Quantifying Bands on a Cel How to Analyze a Movie Tutorial: Counting Vesicles in Cells Particle Tracking Tutorial: Manual Particle Tracking Tutorial: Automated Particle Tracking Kymographs Tutorial: Generating a Kymograph Colocalization Tutorial: Using R to Measure Colocalization over Time Getting the Right Data Out of the Image Validation Back to Square One Golden Rules 5. Statistics 32 33 33 34 34 35 36 37 37 38 40 41 42 44 46 48 48 48 50 50 51 51 53 55 57 58 58 59 61 Designing an Experiment 61 What Is n? Golden Rules 62 65 65 65 67 71 71 Why Does n Matter? Power Analysis for Cell Biologists Basic Statistics That You Will Need A Refresher of Summary Statistics Always Plot Out Your Data
Contents Descriptive Statistics Statistical Tests Compare One Group to a Value Compare Two Groups Comparing Three or More Groups More Complicated Experimental Designs Problems with Data The p-Value What It Really Means Statistically Significant versus Biologically Significant Effect Size Golden Rules 6. Coding Where to Start ix 75 76 76 76 81 85 85 87 87 87 88 89 91 How to Validate and Check Your Data 91 91 92 96 97 98 98 101 102 104 106 109 109 Debugging 112 Getting Help 113 114 114 Basic Principles: Workflow, Reproducibility, and Benefits Mastering the Command Line Getting Started with Coding Variables and Strings Arrays and Vectors Loops How to Write a Basic ImageJ Macro Working on All Files in a Directory Tutorial: Blinding Files for Manual Image Analysis How to Write a Basic R Script for Analysis What Can Go Wrong? Getting Good Ugly Code Write Modular Code Version Control and git Sharing Your Code Golden Rules 7. Putting It Together Plotting Data Best Practice 115 115 117 110 119 119 119
x Contents Making Figures Best Practice Making Figures That Look Great Color Blindness Contrast Adjustments Crops and Expansion Scale Bars Movie Files Unacceptable Manipulation in Figures Golden Rules 122 122 123 125 125 126 126 127 127 128 Appendix: List of Software Featured in This Book 129 Bibliography 131 Index 135
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| discipline | Biologie Informatik |
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| id | DE-604.BV046066003 |
| illustrated | Illustrated |
| indexdate | 2024-12-24T07:45:35Z |
| institution | BVB |
| isbn | 9781621822783 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-031447260 |
| oclc_num | 1137829300 |
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| physical | xiii, 137 Seiten Illustrationen, Diagramme |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | Cold Spring Harbor Laboratory Press |
| record_format | marc |
| spellingShingle | Royle, Stephen J. The digital cell cell biology as a data science Bioinformatik (DE-588)4611085-9 gnd Datenanalyse (DE-588)4123037-1 gnd Cytologie (DE-588)4070177-3 gnd |
| subject_GND | (DE-588)4611085-9 (DE-588)4123037-1 (DE-588)4070177-3 |
| title | The digital cell cell biology as a data science |
| title_auth | The digital cell cell biology as a data science |
| title_exact_search | The digital cell cell biology as a data science |
| title_full | The digital cell cell biology as a data science Stephen J. Royle, University of Warwick |
| title_fullStr | The digital cell cell biology as a data science Stephen J. Royle, University of Warwick |
| title_full_unstemmed | The digital cell cell biology as a data science Stephen J. Royle, University of Warwick |
| title_short | The digital cell |
| title_sort | the digital cell cell biology as a data science |
| title_sub | cell biology as a data science |
| topic | Bioinformatik (DE-588)4611085-9 gnd Datenanalyse (DE-588)4123037-1 gnd Cytologie (DE-588)4070177-3 gnd |
| topic_facet | Bioinformatik Datenanalyse Cytologie |
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