Precedence Temporal Networks to represent temporal relationships in gene expression data

Lucia Sacchi, Cristiana Larizza, Paolo Magni, Riccardo Bellazzi

Research output: Contribution to journalArticlepeer-review

Abstract

The reconstruction of gene regulatory networks from gene expression time series is nowadays an interesting research challenge. A key problem in this kind of analysis is the automated extraction of precedence and synchronization between interesting patterns assumed by genes over time. The present work introduces Precedence Temporal Networks (PTN), a novel method to extract and visualize temporal relationships between genes. PTNs are a special kind of temporal network where nodes represent temporal patterns while edges identify precedence or synchronization relationships between the nodes. The method is tested on two case studies: the expression of a subset of genes in the soil amoeba Dictyostelium discoideum and of a set of well-studied genes involved in the human cell cycle regulation. The extracted networks reflect the capability of the algorithm to clearly reconstruct the timing of the considered gene sets, highlighting different stages in Dictyostelium development and in the cell cycle, respectively.

Original languageEnglish
Pages (from-to)761-774
Number of pages14
JournalJournal of Biomedical Informatics
Volume40
Issue number6
DOIs
Publication statusPublished - Dec 2007

Keywords

  • DNA microarrays
  • Gene expression
  • Temporal Abstraction
  • Temporal association rules
  • Temporal data mining
  • Temporal networks

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics
  • Computer Science (miscellaneous)
  • Catalysis

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