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The question refers to the following table, which compares the percent sequence homology of four different parts (two introns and two exons) of a gene that is found in five different eukaryotic species. Each part is numbered to indicate its distance from the promoter (for example, Intron I is the one closest to the promoter). The data reported for species A were obtained by comparing DNA from one member of species A to another member of species A.
Regarding these sequence homology data, the principle of maximum parsimony would be applicable in ________. (A) distinguishing introns from exons (B) determining degree of sequence homology (C) selecting appropriate genes for comparison among species (D) inferring evolutionary relatedness from the number of sequence differences

Respuesta :

The idea of maximal parsimony would be relevant to this sequence homology data in order to infer evolutionary relatedness from the quantity of sequence differences.

What is homology data?

Topological data analysis (TDA) use the persistent homology (PH) method to examine qualitative characteristics of data that endure across many sizes. It offers a concise representation of the qualitative characteristics of the input, is resistant to perturbations of the input data, and is independent of dimensions and coordinates.

Before conducting further supervised or unsupervised analysis, modern data science employs so-called topological approaches to identify the structural characteristics of data sets. Since geometry may be thought of as the study of distance functions, topology and geometry are highly natural techniques for analyzing large volumes of data.

Topological data analysis, often known as TDA, is a group of techniques that adds new information to datasets.

To learn more about homology data from the given link:

brainly.com/question/13242901

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