Stochastic Distance Between Burkitt Lymphoma/Leukemia Strains

  • Jesús E. García
  • R. Gholizadeh
  • V. A. González López
Chapter
Part of the The Springer Series on Demographic Methods and Population Analysis book series (PSDE, volume 46)

Abstract

Quantifying the proximity between N-grams allows to establish criteria of comparison between them. Recently, a consistent distance d to achieve this end was proposed, see García JE, González-López VA. Detecting regime changes in Markov models. In New trends in stochastic modeling and data analysis (chapter 2, page 103), 2015. This distance takes advantage of a model structure on Markovian processes in finite alphabets and with finite memories, called Partition Markov Models, see García JE, González-López VA. Entropy 19:160, 2017. In this work we explore the performance of d in a real problem, using d to establish a notion of natural proximity between DNA sequences from patients with identical diagnosis, which is: Burkitt lymphoma/leukemia. And we present a robust strategy of estimation to identify the stochastic law that governs most of the sequences considered, thus mapping out a common profile to all these patients, via their DNA sequences.

Keywords

Partition Markov models Bayesian information criterion Robust estimation in stochastic processes 

References

  1. García, J. E., & González-López, V. A. (2015). Detecting regime changes in Markov models. In R. Manca, S. McClean, C. H. Skiadas (Eds) New trends in stochastic modeling and data analysis. Chapter 2, 103. ISAST, Athens, Greece (ISBN: 978-618-5180-06-5) .Google Scholar
  2. García, J. E., & González-López, V. A. (2017). Consistent estimation of partition Markov models. Entropy, 19(4), 160.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Jesús E. García
    • 1
  • R. Gholizadeh
    • 2
  • V. A. González López
    • 1
  1. 1.Department of StatisticsUniversity of CampinasCampinasBrazil
  2. 2.University of CampinasCampinasBrazil

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