Kooperativer Bibliotheksverbund

UID:

Format: 1 Online-Ressource.

ISBN: 978-3-030-22386-1

Series Statement: Learning materials in biosciences

Additional Edition: Erscheint auch als Druck-Ausgabe, Paperback ISBN 978-3-030-22385-4

Additional Edition: Erscheint auch als Druck-Ausgabe, MyCopy Softcover ISBN 978-3-030-22387-8

Language: English

Subjects: Computer Science

Keywords: Biomedizin ; Bioinformatik ; Daten

DOI: 10.1007/978-3-030-22386-1

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)

Author information: Miura, Kota 1969-

UID:

Format: 1 Online-Ressource.

ISBN: 978-3-030-22386-1

Series Statement: Learning materials in biosciences

Additional Edition: Erscheint auch als Druck-Ausgabe, Paperback ISBN 978-3-030-22385-4

Additional Edition: Erscheint auch als Druck-Ausgabe, MyCopy Softcover ISBN 978-3-030-22387-8

Language: English

Subjects: Computer Science

Keywords: Biomedizin ; Bioinformatik ; Daten

DOI: 10.1007/978-3-030-22386-1

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)

Author information: Miura, Kota, 1969-

UID:

Format: 1 Online-Ressource.

ISBN: 978-3-030-22386-1

Series Statement: Learning materials in biosciences

Additional Edition: Erscheint auch als Druck-Ausgabe, Paperback ISBN 978-3-030-22385-4

Additional Edition: Erscheint auch als Druck-Ausgabe, MyCopy Softcover ISBN 978-3-030-22387-8

Language: English

Subjects: Computer Science

Keywords: Biomedizin ; Bioinformatik ; Daten

DOI: 10.1007/978-3-030-22386-1

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)

Author information: Miura, Kota 1969-

UID:

Format: 1 Online-Ressource.

ISBN: 978-3-030-22386-1

Series Statement: Learning materials in biosciences

Additional Edition: Erscheint auch als Druck-Ausgabe, Paperback ISBN 978-3-030-22385-4

Additional Edition: Erscheint auch als Druck-Ausgabe, MyCopy Softcover ISBN 978-3-030-22387-8

Language: English

Subjects: Computer Science

Keywords: Biomedizin ; Bioinformatik ; Daten

DOI: 10.1007/978-3-030-22386-1

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)

Author information: Miura, Kota 1969-

UID:

Format: 1 online resource (170)

Edition: 1st ed. 2020.

ISBN: 3-030-22386-8

Series Statement: Learning Materials in Biosciences,

Content: This Open Access textbook provides students and researchers in the life sciences with essential practical information on how to quantitatively analyze data images. It refrains from focusing on theory, and instead uses practical examples and step-by step protocols to familiarize readers with the most commonly used image processing and analysis platforms such as ImageJ, MatLab and Python. Besides gaining knowhow on algorithm usage, readers will learn how to create an analysis pipeline by scripting language; these skills are important in order to document reproducible image analysis workflows. The textbook is chiefly intended for advanced undergraduates in the life sciences and biomedicine without a theoretical background in data analysis, as well as for postdocs, staff scientists and faculty members who need to perform regular quantitative analyses of microscopy images.

Note: Workflows and Components of Bioimage Analysis -- Measurements of Intensity Dynamics at the Periphery of the Nucleus -- 3D Quantitative Colocalisation Analysis -- The NEMO Dots Assembly: Single-Particle Tracking and Analysis -- Introduction to MATLAB: Image Analysis & Brownian Motion -- Resolving the process of Clathrin Mediated Endocytosis Using Correlative Light & Electron Microscopy (CLEM). , English.

Additional Edition: ISBN 3-030-22385-X

Language: English

DOI: 10.1007/978-3-030-22386-1

URL: kostenfrei

URL: Cover

UID:

Format: 1 Online-Ressource (170 p.)

ISBN: 9783030223861

Series Statement: Learning Materials in Biosciences

Content: This Open Access textbook provides students and researchers in the life sciences with essential practical information on how to quantitatively analyze data images. It refrains from focusing on theory, and instead uses practical examples and step-by step protocols to familiarize readers with the most commonly used image processing and analysis platforms such as ImageJ, MatLab and Python. Besides gaining knowhow on algorithm usage, readers will learn how to create an analysis pipeline by scripting language; these skills are important in order to document reproducible image analysis workflows. The textbook is chiefly intended for advanced undergraduates in the life sciences and biomedicine without a theoretical background in data analysis, as well as for postdocs, staff scientists and faculty members who need to perform regular quantitative analyses of microscopy images

Note: English

Language: English

URL: kostenfrei

UID:

Format: 1 online resource (178 pages)

Edition: 1st ed.

ISBN: 9783030223861

Series Statement: Learning Materials in Biosciences Series

Note: Intro -- Preface -- Acknowledgements -- Contents -- Contributors -- 1: Workflows and Components of Bioimage Analysis -- 1.1 Introduction -- 1.2 Types of Bioimage Analysis Software -- Bibliography -- 2: Measurements of Intensity Dynamics at the Periphery of the Nucleus -- 2.1 Introduction -- 2.2 Tools -- 2.3 Dataset -- 2.4 Workflow -- 2.4.1 Segmentation of Nucleus Rim -- 2.4.1.1 Block 1: Splitting Channels -- 2.4.1.2 Block 2: Segmentation of Nucleus Rim -- 2.4.1.3 Block 3: Intensity Measurement Using Mask -- 2.4.2 Integration: The Measurement Over Time -- 2.4.3 Integrating Segmentation and Measurements -- 2.5 Results and Conclusion -- 2.6 Exercise Answers -- 2.6.1 Exercises 2.1-2.4 -- 2.6.2 Exercise 2.5 -- Bibliography -- 3: 3D Quantitative Colocalisation Analysis -- 3.1 Introduction -- 3.1.1 What Is Colocalisation? -- 3.1.2 Which Colocalisation Methods Are There? -- 3.1.3 Some Image Preprocessing Tips You Should Keep in Mind -- 3.2 Datasets -- 3.3 Tools -- 3.4 Workflow 1: Objects Overlap Volume Quantification -- 3.4.1 Step 0: Building a Strategy -- 3.4.2 Step 1: Normalize the Image Names -- 3.4.3 Step 2: Tag the Objects -- 3.4.4 Step 3: Isolating the Overlapping Parts -- 3.4.5 Step 4: Retrieve Volumes -- 3.4.6 Step 5: Generate Outputs -- 3.4.7 Step 6: Make the Macro User Friendly -- 3.4.8 What Then? -- 3.5 Workflow 2: Objects Overlap Intensity Quantification -- 3.5.1 What Should We Do? -- 3.5.2 New Step 4: Retrieve Intensities -- 3.5.3 Adapted Step 6: Make the Macro User Friendly -- Bibliography -- 4: The NEMO Dots Assembly: Single-Particle Tracking and Analysis -- 4.1 Introduction -- 4.2 Datasets -- 4.3 Tools and Prerequisites -- 4.4 Workflow -- 4.5 Single-Particle Tracking with TrackMate -- 4.5.1 Step 1: Loading Image Data and Launching TrackMate -- 4.5.2 Step 2: Detection -- 4.5.3 Step 3: Filtering. , 4.5.4 Step 4: Particle-Linking -- 4.5.5 Step 5: Filtering Tracks -- 4.5.6 Step 6: Export Results -- 4.6 Motility Analysis with Mean-Square Displacement -- 4.6.1 Step 1: Importing Tracks into MATLAB -- 4.6.2 Step 2: Create and Add Data to the MSD Analyzer -- 4.6.3 Interlude: A Short Word About Mean-Square Displacement Analysis -- 4.6.4 Step 3: Compute the Mean-Square Displacement -- 4.6.5 Step 4: Log-Log Fit of the Mean-Square Displacement -- 4.6.6 Step 5: Analysis of the Log-Log Fit -- 4.7 Results and Conclusion -- Bibliography -- 5: Introduction to MATLAB -- 5.1 Tools -- 5.1.1 MATLAB -- 5.1.2 Image Processing Toolbox -- 5.1.3 Statistics and Machine Learning Toolbox, Curve Fitting Toolbox -- 5.2 Getting Started with MATLAB -- 5.2.1 Baby Steps -- 5.2.2 Plot Something -- 5.2.3 Make it Pretty -- 5.2.4 Getting Help -- 5.3 Automating It: Creating Your Own Programs -- 5.3.1 Create, Save, and Run Scripts -- 5.3.2 Code Folding and Block-Wise Execution -- 5.3.3 Scripts, Programs, Functions: Nomenclature -- 5.4 Working with Images -- 5.4.1 Reading and Displaying an Image -- 5.4.2 Extracting Meta-Data from an Image -- 5.4.3 Reading and Displaying an Image-Stack -- 5.4.4 Smoothing, Thresholding and All That -- 5.5 Time-Series Analysis -- 5.5.1 Simulating a Time-Series of Brownian Motion (Random Walk) -- 5.5.2 Plotting a Time-Series -- 5.5.3 Histograms -- 5.5.4 Sub-Sampling a Time-Series (Slicing and Accessing Data) -- 5.5.5 Investigating How "Speed" Depends on Δt -- 5.5.6 Investigating How "Speed" Depends on Subsampling -- 5.5.7 Simulating Confined Brownian Motion -- 5.5.8 Simulating Directed Motion with Random Tracking Error -- 5.5.9 Loading Tracking Data from a File -- 5.5.10 Smoothing (Filtering) a Time-Series -- 5.6 MSD: Mean Square Displacement -- 5.6.1 Creating a Function That Calculates MSDs. , 5.6.1.1 About Functions and How to Call Them -- 5.6.2 MSD: Linear Motion -- 5.6.3 MSD: Brownian Motion -- 5.6.3.1 MSD: Simulated Random Walk -- 5.6.4 MSD: Averaged Over Several 2-Dim Tracks -- 5.6.5 Further Reading About Diffusion, the MSD, and Fitting Power-Laws -- Appendix: MATLAB Fundamental Data Classes -- MATLAB Documentation Keywords for Data Classes -- Appendix: Do I Have That Toolbox? -- Appendix: HTML and Live Scripts -- Publish Your Script to HTML -- Working with Live Scripts -- Appendix: Getting File and Folder Names Automatically -- Read from a Folder -- Path and File Names -- Appendix: Codehygiene -- Appendix: MATLAB Cheat Sheet -- Bibliography -- 6: Resolving the Process of Clathrin Mediated Endocytosis Using Correlative Light and Electron Microscopy (CLEM) -- 6.1 Introduction -- 6.2 Data Presentation -- 6.3 Overview of Data Processing -- 6.4 Tools Description -- 6.5 Application to a CLEM Experiment -- 6.5.1 CLEM Workflow Overview and Preparation -- 6.5.2 Labeling of Landmark Pairs -- 6.5.2.1 Correlation from Low Magnification Tomogram to High Magnification EM Image -- 6.5.3 Generating the Transformation -- 6.5.4 Applying the Transformation to Image and Coordinate Data -- 6.5.4.1 Transforming Images -- 6.5.4.2 Transforming Coordinates -- 6.5.5 Registering the Low-Magnification and the High-Magnification EM Data -- 6.6 Accuracy Estimation and Improvements -- Appendix: Image Transformations -- Basic Similarity and Affine Transformations -- Higher-Order Transformations -- Generating Transformations from Image Coordinates -- Bibliography -- Index.

Additional Edition: Print version: Miura, Kota Bioimage Data Analysis Workflows Cham : Springer International Publishing AG,c2019 ISBN 9783030223854

Language: English

Keywords: Electronic books.

URL: Click to View

URL: lizenzpflichtig

UID:

Format: 1 online resource (x, 170 pages) : , illustrations (some color)

ISBN: 9783030223861 , 3030223868

Series Statement: Learning materials in biosciences,

Content: This Open Access textbook provides students and researchers in the life sciences with essential practical information on how to quantitatively analyze data images. It refrains from focusing on theory, and instead uses practical examples and step-by step protocols to familiarize readers with the most commonly used image processing and analysis platforms such as ImageJ, MatLab and Python. Besides gaining knowhow on algorithm usage, readers will learn how to create an analysis pipeline by scripting language; these skills are important in order to document reproducible image analysis workflows. The textbook is chiefly intended for advanced undergraduates in the life sciences and biomedicine without a theoretical background in data analysis, as well as for postdocs, staff scientists and faculty members who need to perform regular quantitative analyses of microscopy images.

Note: Workflows and Components of Bioimage Analysis -- Measurements of Intensity Dynamics at the Periphery of the Nucleus -- 3D Quantitative Colocalisation Analysis -- The NEMO Dots Assembly: Single-Particle Tracking and Analysis -- Introduction to MATLAB: Image Analysis & Brownian Motion -- Resolving the process of Clathrin Mediated Endocytosis Using Correlative Light & Electron Microscopy (CLEM). , English.

Additional Edition: ISBN 303022385X

Language: English

Keywords: Index not Present.

DOI: 10.1007/978-3-030-22386-1

URL: ProQuest Ebook Central

URL: SpringerLink

UID:

Format: ix, 170 Seiten.

ISBN: 978-3-030-22385-4

Series Statement: Learning materials in biosciences

Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-3-030-22386-1

Language: English

Subjects: Computer Science

Keywords: Biomedizin ; Bioinformatik ; Daten

Author information: Miura, Kota, 1969-

UID:

Format: 1 online resource (170)

Edition: 1st ed. 2020.

ISBN: 3-030-22386-8

Series Statement: Learning Materials in Biosciences,

Content: This Open Access textbook provides students and researchers in the life sciences with essential practical information on how to quantitatively analyze data images. It refrains from focusing on theory, and instead uses practical examples and step-by step protocols to familiarize readers with the most commonly used image processing and analysis platforms such as ImageJ, MatLab and Python. Besides gaining knowhow on algorithm usage, readers will learn how to create an analysis pipeline by scripting language; these skills are important in order to document reproducible image analysis workflows. The textbook is chiefly intended for advanced undergraduates in the life sciences and biomedicine without a theoretical background in data analysis, as well as for postdocs, staff scientists and faculty members who need to perform regular quantitative analyses of microscopy images.

Note: Workflows and Components of Bioimage Analysis -- Measurements of Intensity Dynamics at the Periphery of the Nucleus -- 3D Quantitative Colocalisation Analysis -- The NEMO Dots Assembly: Single-Particle Tracking and Analysis -- Introduction to MATLAB: Image Analysis & Brownian Motion -- Resolving the process of Clathrin Mediated Endocytosis Using Correlative Light & Electron Microscopy (CLEM). , English.

Additional Edition: ISBN 3-030-22385-X

Language: English

DOI: 10.1007/978-3-030-22386-1