Cluster Switches in Gene Expression Data

Maayan Hassidim, Guy Shani, Tal Shay

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Following the sequencing of the human genome, the next step is to understand the function of all genes in health and disease. However, experimental study of the functions of all genes in all diseases is impossible and unnecessary, as not all genes are functional in all conditions. However, understanding which genes are functional in each condition and how they are regulated requires a laborious and expensive experimental effort. In this paper we suggest a heuristic framework, CSGI (cluster switching genes identification) for identifying promising genes for thorough analysis. In CSGI we project a cluster defined in one context to its projection in another context, identifying genes that behave differently in different contexts.We provide a case study of immune system clusters showing that our approach identifies clusters representing core conserved biological processes, as well as important genes that switch of clusters.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
EditorsHarald Schmidt, David Griol, Haiying Wang, Jan Baumbach, Huiru Zheng, Zoraida Callejas, Xiaohua Hu, Julie Dickerson, Le Zhang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1788-1795
Number of pages8
ISBN (Electronic)9781538654880
DOIs
StatePublished - 21 Jan 2019
Event2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 - Madrid, Spain
Duration: 3 Dec 20186 Dec 2018

Publication series

NameProceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

Conference

Conference2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
Country/TerritorySpain
CityMadrid
Period3/12/186/12/18

Keywords

  • Clustering
  • RNA sequencing
  • co-expression
  • microarray
  • regulation
  • transcriptomics

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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