The Digital Cell: Cell Biology as a Data Science

The Digital Cell: Cell Biology as a Data Science

Cell and molecular biology are becoming increasingly data driven. Technological advances and increased computing power mean that researchers now increasingly quantify experimental results, rather than simply report qualitative, representative observations. The Digital Cell provides a comprehensive guide for scientists seeking to make this transition. It describes how data should be generated and processed, discussing research workflows, pipelines, and storage solutions. A key focus of the book is imaging—image types and formats are explained, as is software for image processing and analysis, along with techniques such as segmentation analysis and automated particle tracking.

The book examines the wide variety of statistical approaches that can be used for data analysis, emphasizing concepts such as significance and reproducibility. It also includes an introduction to coding, including examples of how to write and use R scripts to analyze results. In addition, there is useful advice on how to plot and present data to convey results most effectively. The Digital Cell is thus an essential resource for all cell and molecular biologists—from students embarking on research for the first time to experienced scientists who need to acquire, process, and present their data accurately and efficiently.

Download a Free Excerpt from The Digital Cell: Cell Biology as a Data Science:

Preface
The Digital Cell Philosophy
Index

More INFO Below

Description
Contents

Description

Add this Title to Order List

Preface
Acknowledgments
1. The Digital Cell Philosophy: Workflows and Pipelines; Using Spreadsheets for Experimental Data; Software for Digital Cell Biology; Focusing on Imaging; Golden Rules
2. Dealing with Data: Why Is Organization So Important?; Getting Organized; 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; Fiji; RStudio; What Is an Image?; Image Formats; Image Types; Multidimensional Image Files; Metadata; Image Transformation; 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; Gel Densitometry; Tutorial: Quantifying Bands on a Gel; 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: Designing an experiment; What Is n?; Golden Rules; 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; 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; 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?; How to Validate and Check Your Data; Debugging; Getting Help; Getting Good; Ugly Code; Write Modular Code; Version Control and git; Sharing Your Code; Golden Rules
7. Putting It Together: Plotting Data; Best Practice; 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
Appendix: List of Software Featured in This Book
Bibliography
Index

$54.87
This bundle includes the following products:

The Digital Cell: Cell Biology as a Data Science