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R for Biologists: Learn R programming from scratch | No prior coding experience required | An absolute beginner's guide (Biotechnology Books)
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Unlock the power of data analysis with R, designed specifically for biologists like you!
This book "R for Biologists: Learn R Programming from Scratch" is designed specifically for biologists with no prior programming experience. Whether you're a student, researcher, or professional, this comprehensive guide will provide you with a solid foundation in R, enabling you to handle and analyze biological data with confidence.
Why choose this book?This book is your hands-on introduction to R programming, crafted with the understanding that you have no prior coding experience. Each chapter is a carefully structured step forward, building on what you've learned and guiding you through practical, real-world biological examples. By following along with code-along exercises, you'll see exactly how to apply new concepts as you learn them.
Who is this book for?- Biologists with no prior programming experience
- Students, researchers, and professionals looking to enhance their data analysis skills
- Anyone eager to learn R from the ground up, with no prerequisites required
You don't need any background in programming or even R installed on your computer to get started—this book will guide you through every step, from installation to advanced analysis.
What you will learn:By the end of this book, you'll have mastered:
- Installing and configuring R and RStudio on your computer
- Understanding fundamental R programming concepts, including variables, data types, and functions
- Writing and executing R scripts to streamline your tasks
- Organizing and managing biological data with vectors, matrices, lists, and data frames
- Summarizing and restructuring complex datasets
- Creating publication-quality visualizations of your data using ggplot2, including scatter plots, bar charts, histograms, and more
- Reading and importing data from CSV, Excel, and FASTA files into R
- Harnessing the power of packages like 'dplyr' and 'tidyverse' to efficiently organize, transform, and prepare biological data for analysis
- Conducting genome sequence analysis using Bioconductor packages
- Performing RNA-Seq data analysis, from normalization to differential expression
- Tackling real-world biological datasets with confidence
Why Learning R is Easier Than You Think
Learning R is like learning a new language—it requires patience and practice, but with the right guide, it's a journey that can be both enjoyable and immensely rewarding. "R for Biologists: Learn R Programming from Scratch" makes the learning process accessible, practical, and directly applicable to your field.
Get Started TodayDon't just read about R—experience it. Dive into "R for Biologists: Learn R Programming from Scratch" and equip yourself with the skills to analyze and visualize your data like never before. Whether you're looking to boost your research, enhance your studies, or simply broaden your skillset, this book is the perfect starting point.
- ISBN-109334098767
- ISBN-13978-9334098761
- Publication dateAugust 15, 2024
- LanguageEnglish
- Dimensions6 x 1.09 x 9 inches
- Print length480 pages
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Product details
- Publisher : Roohi Bansal
- Publication date : August 15, 2024
- Language : English
- Print length : 480 pages
- ISBN-10 : 9334098767
- ISBN-13 : 978-9334098761
- Item Weight : 1.77 pounds
- Dimensions : 6 x 1.09 x 9 inches
- Part of series : Biotechnology Books
- Best Sellers Rank: #149,764 in Books (See Top 100 in Books)
- #3 in Bioinformatics (Books)
- #6 in Biostatistics (Books)
- #68 in Introductory & Beginning Programming
- Customer Reviews:
About the author

Roohi Bansal, PhD, is the founder of Techskill Brew (techskillbrew.com), an online platform where she creates educational content in the form of blogs and videos. With her passion for teaching, she has inspired and taught more than 13,000 students from 120+ countries.
She earned her PhD from the CSIR-Institute of Microbial Technology, India. Her research was focused on Mycobacterium tuberculosis, the bacterial pathogen that causes tuberculosis. Her work has been published in reputed peer-reviewed scientific journals, including Molecular Microbiology and Journal of Biological Chemistry, among others.
Customer reviews
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Not worth your time or money
Top reviews from the United States
- 5 out of 5 stars
R for Biologists book
Reviewed in the United States on December 26, 2025The author has done a very good job presenting this topic. Some very good insights.
Sending feedback...Sending feedback...HelpfulThank you for your feedback.Sorry, we failed to record your vote. Please try againThanks, we'll investigate in the next few days.Sorry, We failed to report this review. Please try again - 3 out of 5 stars
Good starter book.
Reviewed in the United States on April 3, 2026Does not cover Loops.
Easy to read, but some examples are sketchy.
Has a lot of good basics.
Sending feedback...Sending feedback...HelpfulThank you for your feedback.Sorry, we failed to record your vote. Please try againThanks, we'll investigate in the next few days.Sorry, We failed to report this review. Please try again - 5 out of 5 stars
Great book for a beginner
Reviewed in the United States on October 5, 2025This is excellent
Sending feedback...Sending feedback...HelpfulThank you for your feedback.Sorry, we failed to record your vote. Please try againThanks, we'll investigate in the next few days.Sorry, We failed to report this review. Please try again - 1 out of 5 stars
Not worth your time or money
Reviewed in the United States on May 31, 2026This is without a doubt the worst book I've ever read, and that's really saying something because I've been pretty adventurous with the technical books I've purchased. It was truly a struggle to read this, but I persisted from cover to cover. I'll keep most of the review brief because the attached image covers most of what I want to say well. The book is very low quality in several dimensions.
First, the typesetting is awful. If you've read many technical books, you might be used to some kind of code formatting, usually with a monospace font and/or some kind of textbox or background color (sometimes even syntax highlighting) to differentiate it from the prose. As you can see here, neither the inline code nor the blocks of code use a different style, and the code example is even justified across the width of the page. You might think this is a minor or superficial issue, and to some extent that's true, but this book has code examples on every single page, and it's presented either as oddly wrapped and spaced text that looks just like the prose or as screenshots of RStudio, as you can also see in the image.
The second major issue is the writing itself, which is mind-numbingly repetitive. Actually the picture cuts part of this off, unfortunately, but just read section 12.6 here.
> mean_sepal_length = mean(Sepal.Length): Computes the mean of the Sepal.Length...
This is not an isolated example. I took this photo after turning to a random page. This is what the whole book is like.
This leads into the final problem that I'll touch on, which is that the book covers every subject at approximately the same level of depth. This means that there's an entire chapter dedicated to navigating the RStudio installer on Windows at the start and a whole chapter dedicated to changing the working directory (near the end!), but actually important aspects of R or using R for biological analysis are kind of skimmed over. Maybe "at the same level" is being too generous. After writing that previous sentence it seems clear that minutiae like clicking through an installer is given far more prominence than the apparent goal of the book (learning R).
This book will not teach you R, and it will certainly not teach you to program. Even worse, it will try to bore you to tears on the way to nowhere. If you're looking to learn R, I would highly recommend just reading through the free documentation on the R website, and if you really want a book, checking out the list they provide there. To the extent that this book contains useful information, you'll find it in a much better form just about anywhere else.

This is without a doubt the worst book I've ever read, and that's really saying something because I've been pretty adventurous with the technical books I've purchased. It was truly a struggle to read this, but I persisted from cover to cover. I'll keep most of the review brief because the attached image covers most of what I want to say well. The book is very low quality in several dimensions.
First, the typesetting is awful. If you've read many technical books, you might be used to some kind of code formatting, usually with a monospace font and/or some kind of textbox or background color (sometimes even syntax highlighting) to differentiate it from the prose. As you can see here, neither the inline code nor the blocks of code use a different style, and the code example is even justified across the width of the page. You might think this is a minor or superficial issue, and to some extent that's true, but this book has code examples on every single page, and it's presented either as oddly wrapped and spaced text that looks just like the prose or as screenshots of RStudio, as you can also see in the image.
The second major issue is the writing itself, which is mind-numbingly repetitive. Actually the picture cuts part of this off, unfortunately, but just read section 12.6 here.
> mean_sepal_length = mean(Sepal.Length): Computes the mean of the Sepal.Length...
This is not an isolated example. I took this photo after turning to a random page. This is what the whole book is like.
This leads into the final problem that I'll touch on, which is that the book covers every subject at approximately the same level of depth. This means that there's an entire chapter dedicated to navigating the RStudio installer on Windows at the start and a whole chapter dedicated to changing the working directory (near the end!), but actually important aspects of R or using R for biological analysis are kind of skimmed over. Maybe "at the same level" is being too generous. After writing that previous sentence it seems clear that minutiae like clicking through an installer is given far more prominence than the apparent goal of the book (learning R).
This book will not teach you R, and it will certainly not teach you to program. Even worse, it will try to bore you to tears on the way to nowhere. If you're looking to learn R, I would highly recommend just reading through the free documentation on the R website, and if you really want a book, checking out the list they provide there. To the extent that this book contains useful information, you'll find it in a much better form just about anywhere else.
Sending feedback...Sending feedback...HelpfulThank you for your feedback.Sorry, we failed to record your vote. Please try againThanks, we'll investigate in the next few days.Sorry, We failed to report this review. Please try again - 4 out of 5 stars
Useful book
Reviewed in the United States on April 9, 2025A helpful and approachable guide for biologists with no coding background.
The book explains R concepts in a simple, easy-to-understand manner.
Great for absolute beginners in life sciences and biotechnology.
Some parts could use more depth, but overall a solid introduction.
Sending feedback...Sending feedback...HelpfulThank you for your feedback.Sorry, we failed to record your vote. Please try againThanks, we'll investigate in the next few days.Sorry, We failed to report this review. Please try again















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