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Detection of Age-Related Changes in Networks of B Cells by Multivariate Time-Series Analysis

  • Alberto CastelliniEmail author
  • Giuditta Franco
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10710)

Abstract

Immunosenescence concerns the gradual deterioration of the immune system due to aging. Recent advances in cellular phenotyping have enabled key improvements in this context during the last decades. In this work we present a novel extensions and integration of data-driven models for describing age-related changes in the network of relationships among cell quantities of eight peripheral B lymphocyte subpopulations. Our dataset contains about six thousands samples of patients having an age between one day and ninety-six years, where for each patient, cell quantities of eight peripheral B lymphocyte subpopulations were measured. By correlation-based multiple time series segmentation we generate four sets of age-related networks depending on the number of age segments. We first analyze a partition in 30 very short segments, then segmentations in 5, 3 and 2 segments. Moving from a fine to a large grain segmentation, different aspects of the dataset are highlighted and analyzed.

Notes

Acknowledgments

Authors would like to thank Antonio Vella (department of pathology and diagnostics, University Hospital of Verona) for providing the dataset used in this work and for interesting discussions on the role of B cells in the immune system.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceVerona UniversityVeronaItaly

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