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Computational Biology

Introduction to Computational Cancer Biology

By Kenwright

Explore how computational methods are transforming cancer biology and driving innovation in oncology.

WHAT THE PUBLISHER HIGHLIGHTS

  • Understand how data science is applied to cancer biology.
  • Learn key computational techniques used in oncology research.
  • Explore real-world applications of bioinformatics in cancer treatment.

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INSIDE THE BOOK

About this book

Cancer is one of the most complex diseases known to science, and understanding it requires more than biology alone. This book introduces readers to the powerful role of computational techniques in cancer research. From modeling tumor growth and analyzing genomic data to applying machine learning for diagnosis and treatment prediction, this guide offers a comprehensive overview of the tools and technologies reshaping oncology. Designed for students, researchers, and clinicians, it bridges the gap between biological insight and computational power.

From the publisher’s description

  • Understand how data science is applied to cancer biology.
  • Learn key computational techniques used in oncology research.
  • Explore real-world applications of bioinformatics in cancer treatment.
  • Gain insights into the future of personalized medicine.

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ANOTHER PERSPECTIVE

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Reader review4

Good, but not for absolute beginners

Good value. Not perfect, but I would buy another book from this author.

I have been working with computational biology for a few years now and I still found plenty here that was new to me. It is denser than the page count suggests, and I found myself slowing down around the middle. The balance between theory and practice is well judged; neither side dominates. Worth picking up if you already have the basics. Set realistic expectations and you will get a lot out of it.

Sofia JohnsonMLOps engineer · Stockholm, SE
Introduction to Computational Cancer Biology
Reader review5

Highly recommended

Better than I expected. Rare to find a technical book this well judged.

I had been on the fence about this one for a while, and I should have bought it sooner. It is denser than the page count suggests, and I found myself slowing down around the middle. The examples are small enough to type out and experiment with, which is exactly what I want from a book like this. The balance between theory and practice is well judged; neither side dominates. An easy five stars from me. I look forward to whatever the author writes next.

Andrew TurnerCloud architect · Rome, IT
Introduction to Computational Cancer Biology
Reader review3

Useful in parts

Not quite what I expected from the description, but there is material here.

I picked this up after getting stuck on a project and it turned out to be exactly the right book at the right time. I particularly liked the way the author builds up from simple cases before introducing the harder material. The progression from chapter to chapter is well thought out; nothing feels out of order. The book rewards careful reading. Skimming it would be a mistake. Useful as a reference, less so as a straight read from cover to cover.

Kate WhiteUniversity lecturer · Seoul, KR
Introduction to Computational Cancer Biology

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