A network-based approach to mine temporal genes exhibiting significant expression variation in Caenorhabditis elegans

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

It is critical to be able to identify longitudinally changing genes in temporal data so that studies can be focused on how gene expression changes in a dynamic way. While biological networks continue to play a significant role in modeling and characterizing complex relationships in biological systems, most network modeling studies in biomedical research focus on snapshot or 'static' network-based analysis to identify genes of interest. In this study, we use a temporal non-sampling network-based approach to identify and rank genes that exhibit significant co-expression variation over time. We use in the C. elegans gene correlation network obtained from mRNA expression profiles to illustrate the value of the proposed approach. We compare the results of this method to results obtained from traditional statistical analysis that focuses on identifying simple differentially expressed genes. We show that rank-based temporal network analysis can identify genes that contribute to changes in the network structure and consequently contribute to changes in the genetic regulatory machine.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
EditorsIllhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2151-2156
Number of pages6
ISBN (Electronic)9781509030491
DOIs
StatePublished - Dec 15 2017
Event2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States
Duration: Nov 13 2017Nov 16 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume2017-January

Other

Other2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
CountryUnited States
CityKansas City
Period11/13/1711/16/17

Keywords

  • bioinformatics algorithms
  • co-expression networks
  • gene expression
  • temporal network analysis

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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