Using flux theory in dynamic omics data sets to identify differentially changing signals using DPoP

Abstract Background Derivative profiling is a novel approach to identify differential signals from dynamic omics data sets. This approach applies variable step-size differentiation to time dynamic omics data. This work assumes that there is a general omics derivative that is a useful and descriptive...

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Bibliographic Details

Published in:	BMC Bioinformatics
Main Authors:	Harley Edwards, Joseph Zavorskas, Walker Huso, Alexander G. Doan, Caton Silbiger, Steven Harris, Ranjan Srivastava, Mark R. Marten
Format:	Article
Language:	English
Published:	BMC 2024-09-01
Subjects:	Dynamic omics analysis Time series analysis Transcriptomic Proteomic Phosphoproteomic Differential signal identification
Online Access:	https://doi.org/10.1186/s12859-024-05938-9