Is algebraic statistics nonsense or useful?

  • Thread starter glaucousNoise
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In summary, the conversation discusses the recurrence of notions of symmetry in bioinformatic and biophysical problems, particularly in protein conformational change. The paper by Sturmfels and Pachter explores the application of this principle to larger biological systems, and the individual speaking is unable to fully understand the concepts due to their lack of background knowledge. They also mention a book, "Life on the Edge" by Johnjoe McFadden, which helped provide context for them in this area.
  • #1
glaucousNoise
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Hi all,

I've been thinking about bioinformatic and biophysical problems, and have noticed that notions of symmetry keep cropping up. An obvious example would be protein conformational change, since the correlations between atoms induce reductions in the entropy of the system via degeneracy (although this is too unwieldy to exploit it seems). However I was wondering if this principle applied to even larger scale biological systems. In poking around the interwebs, I found this very dense and curious paper by Sturmfels:

http://arxiv.org/abs/0904.4529

as well as this more theory oriented paper by him and Lior Pachter:

http://www.pnas.org/content/101/46/16132.short

I don't have the background to understand this stuff. I wanted to know if anybody thought there was anything to it, or if it is just another useless method.
 
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  • #3
intriguing, not exactly what I was looking for but interesting all the same
 

Related to Is algebraic statistics nonsense or useful?

1. Is algebraic statistics a legitimate field of study?

Yes, algebraic statistics is a legitimate field of study that combines techniques from algebra and statistics to develop methods for analyzing data and making statistical inferences.

2. What are some real-world applications of algebraic statistics?

Algebraic statistics has applications in various fields such as genetics, machine learning, and social sciences. It can be used to model and analyze complex data sets, develop efficient algorithms for data analysis, and make predictions based on data.

3. How does algebraic statistics differ from traditional statistics?

Algebraic statistics differs from traditional statistics in that it utilizes algebraic techniques, such as polynomial equations and algebraic geometry, to analyze data instead of relying solely on traditional statistical methods. This allows for a more comprehensive and efficient analysis of complex data sets.

4. Can algebraic statistics be used for both qualitative and quantitative data?

Yes, algebraic statistics can be used for both qualitative and quantitative data. It provides a framework for analyzing data regardless of its type or structure, making it a versatile tool for data analysis.

5. How can I learn more about algebraic statistics?

There are many resources available for learning about algebraic statistics, including textbooks, online courses, and research papers. Some universities also offer courses or programs specifically focused on algebraic statistics. It is recommended to have a strong foundation in both algebra and statistics before delving into this field of study.

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