Show HN: Applying Maths in the Chemical and Biomolecular Sciences(chemistry-maths-book.com)
chemistry-maths-book.com
Show HN: Applying Maths in the Chemical and Biomolecular Sciences
https://chemistry-maths-book.com/intro.html
2 comments
This book seems to pathologically want to keep its contents secret.
Having read the marketing website and GitHub code I am still unsure what chemical and biomolecular subjects it covers.
The file headings are arranged by the math topics and the toc file back references the directory names.
I guess I’ll have to build it to know if the book covers protein folding?
Having read the marketing website and GitHub code I am still unsure what chemical and biomolecular subjects it covers.
The file headings are arranged by the math topics and the toc file back references the directory names.
I guess I’ll have to build it to know if the book covers protein folding?
Okay. I've built it.
It is more math heavy than Chemical and Biomedical heavy. Many chapters and exercises can be wholly devoid of Chemical or Biomedical applications.
I'd say it's more of a "maths you might use in Chemical and Biomedical applications" book.
For the sake of answering my own question, there is one Exercise that deals with a narrow application of protein folding, specifically, forced protein unfolding, in Chapter 3 Differentiation.
The book contains lots of code to use.
Significant focus on using libraries: scipy, numpy, et al; rather than rolling one's own implementation leans it toward high level application knowledge rather than low level intuitive understanding of the mathematical concepts it contains[1].
The exercises come with excellent and thorough solutions.
[1] for the low level roll your own intro to the maths in this book try: Learn Physics with Functional Programming, https://www.lpfp.io/
It is more math heavy than Chemical and Biomedical heavy. Many chapters and exercises can be wholly devoid of Chemical or Biomedical applications.
I'd say it's more of a "maths you might use in Chemical and Biomedical applications" book.
For the sake of answering my own question, there is one Exercise that deals with a narrow application of protein folding, specifically, forced protein unfolding, in Chapter 3 Differentiation.
The book contains lots of code to use.
Significant focus on using libraries: scipy, numpy, et al; rather than rolling one's own implementation leans it toward high level application knowledge rather than low level intuitive understanding of the mathematical concepts it contains[1].
The exercises come with excellent and thorough solutions.
[1] for the low level roll your own intro to the maths in this book try: Learn Physics with Functional Programming, https://www.lpfp.io/
Source code can be found at: https://github.com/subblue/applying-maths-book