Paper Info
Title
Detection of Age-Related Changes in Networks of B Cells by Multivariate Time-Series Analysis.
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.
Year
DOI
Venue
2017
10.1007/978-3-319-72926-8_49
Lecture Notes in Computer Science
Field
DocType
Volume
Time series,Time-series segmentation,Pattern recognition,Segmentation,Computer science,Multivariate statistics,Immunosenescence,Correlation,Artificial intelligence
Conference
10710
ISSN
Citations 
PageRank 
0302-9743
1
0.36
References 
Authors
9
2
Name
Order
Citations
PageRank
Alberto Castellini16014.16
Giuditta Franco213618.34