Estimating the information content of genetic sequence data

A prominent problem in analysing genetic information has been a lack of mathematical frameworks for doing so. This article offers some new statistical methods to model and analyse information content in proteins, protein families, and their sequences. We discuss how to understand the qualitative aspects of genetic information, how to estimate the quantitative aspects of it, and implement a statistical model where the qualitative genetic function is represented jointly with its probabilistic metric of self-information. The functional information of protein families in the Cath and Pfam databases are estimated using a method inspired by rejection sampling. Scientific work may place these components of information as one of the fundamental aspects of molecular biology.

Automated summary

This article introduces new statistical methods for modeling and analyzing information content in proteins, protein families, and their sequences. It discusses the qualitative and quantitative aspects of genetic information and presents a statistical model that combines genetic function with its probabilistic metric of self-information. The functional information of protein families in the Cath and Pfam databases is estimated using a rejection sampling method. These components of information are considered fundamental aspects of molecular biology.