Paper Info
Title
Discovery Of Relevant Response In Infected Potato Plants From Time Series Of Gene Expression Data
Abstract
The paper presents a methodology for analyzing time series of gene expression data collected from the leaves of potato virus Y (PVY) infected and non-infected potato plants, with the aim to identify significant differences between the two sets of potato plants' characteristic for various time points. We aim at identifying differentially-expressed genes whose expression values are statistically significantly different in the set of PVY infected potato plants compared to non-infected plants, and which demonstrate also statistically significant changes of expression values of genes of PVY infected potato plants in time. The novelty of the approach includes stratified data randomization used in estimating the statistical properties of gene expression of the samples in the control set of non-infected potato plants. A novel estimate that computes the relative minimal distance between the samples has been defined that enables reliable identification of the differences between the target and control datasets when these sets are small. The relevance of the outcomes is demonstrated by visualizing the relative minimal distance of gene expression changes in time for three different types of potato leaves for the genes that have been identified as relevant by the proposed methodology.
Year
DOI
Venue
2019
10.3390/make1010023
MACHINE LEARNING AND KNOWLEDGE EXTRACTION
Keywords
DocType
Volume
gene expression time series, potato virus infections, variance-stabilized data, randomization test, stratified randomization, relative minimal distance of samples
Journal
1
Issue
Citations 
PageRank 
1
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Dragan Gamberger175760.53
Tjasa Stare211.70
Dragana Miljkovic385.97
Kristina Gruden4345.49
Nada Lavrac52004635.45