Bioimage Data Analysis Workflows

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...

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Other Authors: Miura, Kota (Editor), Sladoje, Nataša (Editor)
Format: Book Chapter
Published: Cham Springer Nature 2020
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260 |a Cham  |b Springer Nature  |c 2020 
300 |a 1 electronic resource (170 p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a 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. 
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653 |a Medicine 
653 |a Biomedical engineering 
653 |a Cell biology 
653 |a Bioinformatics 
653 |a Biology-Technique 
653 |a Systems biology 
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