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Books > Science & Mathematics > Biology, life sciences
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Hands-On Data Science for Biologists Using Python (Paperback)
Loot Price: R2,337
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Hands-On Data Science for Biologists Using Python (Paperback)
Expected to ship within 12 - 17 working days
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Hands-on Data Science for Biologists using Python has been
conceptualized to address the massive data handling needs of
modern-day biologists. With the advent of high throughput
technologies and consequent availability of omics data, biological
science has become a data-intensive field. This hands-on textbook
has been written with the inception of easing data analysis by
providing an interactive, problem-based instructional approach in
Python programming language. The book starts with an introduction
to Python and steadily delves into scrupulous techniques of data
handling, preprocessing, and visualization. The book concludes with
machine learning algorithms and their applications in biological
data science. Each topic has an intuitive explanation of concepts
and is accompanied with biological examples. Features of this book:
The book contains standard templates for data analysis using
Python, suitable for beginners as well as advanced learners. This
book shows working implementations of data handling and machine
learning algorithms using real-life biological datasets and
problems, such as gene expression analysis; disease prediction;
image recognition; SNP association with phenotypes and diseases.
Considering the importance of visualization for data
interpretation, especially in biological systems, there is a
dedicated chapter for the ease of data visualization and plotting.
Every chapter is designed to be interactive and is accompanied with
Jupyter notebook to prompt readers to practice in their local
systems. Other avant-garde component of the book is the inclusion
of a machine learning project, wherein various machine learning
algorithms are applied for the identification of genes associated
with age-related disorders. A systematic understanding of data
analysis steps has always been an important element for biological
research. This book is a readily accessible resource that can be
used as a handbook for data analysis, as well as a platter of
standard code templates for building models.
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