The Statistical Analysis of Protein Domain Family Distributions via Jaccard Entropy Measures

R. P. Mondaini () and S. C. de Albuquerque Neto
Additional contact information
R. P. Mondaini: Centre of Technology, COPPE, Federal University of Rio de Janeiro
S. C. de Albuquerque Neto: Centre of Technology, COPPE, Federal University of Rio de Janeiro

A chapter in Trends in Biomathematics: Modeling Cells, Flows, Epidemics, and the Environment, 2020, pp 169-207 from Springer

Abstract: Abstract The present work is part of a research programme of assessment of protein databases by applying statistical analysis of protein domain families and their consequent association into clans. An extensive discussion on the construction of an adequate sample space will lead to support the classification of protein domains in families and clans of the literature. An interesting derivation via the Jaccard entropy measure of a specific variable of the non-dimensional parameter of a Havrda–Charvat entropy measure, which corresponds to the best approximation to a normal distribution, is the most important result to be reported here.

Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-46306-9_13

Ordering information: This item can be ordered from
http://www.springer.com/9783030463069

DOI: 10.1007/978-3-030-46306-9_13

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().