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Sinopsis
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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Acerca del autor
Dr. Kota Miura is a Bioimage Data Analyst and works with various research groups at the EMBL in Heidelberg, Germany. He is also Vice Chair of NEUBIAS (the Network of European Bioimage Analysts).
Natasa Sladoje is an Associate Professor at the Centre for Image Analysis, Department of Information Technology at Uppsala University in Sweden and a Professor at the Faculty of Technical Sciences, University of Novi Sad, in Serbia. She is also an Associate Research Professor at the Mathematical Institute of the Serbian Academy of Sciences and Arts.
De la contraportada
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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Bioimage Data Analysis Workflows (Learning Materials in Biosciences)
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Bioimage Data Analysis Workflows
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ISBN 10: 303022385X
ISBN 13: 9783030223854
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Bioimage Data Analysis Workflows
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Springer Nature Switzerland AG, 2019
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ISBN 13: 9783030223854
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Bioimage Data Analysis Workflows (Paperback)
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ISBN 13: 9783030223854
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Paperback. Condición: new. Paperback. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783030223854
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ISBN 10: 303022385X
ISBN 13: 9783030223854
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Paperback. Condición: New. 2020 ed. 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. Nº de ref. del artículo: LU-9783030223854
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