A conceptual approach to gene expression analysis enhanced by visual analytics

MELO, Cassio, ORPHANIDES, Constantinos, MCLEOD, Kenneth, AUFAIRE, Marie-Aude, ANDREWS, Simon and BURGER, Albert (2013). A conceptual approach to gene expression analysis enhanced by visual analytics. In: Proceedings of the 28th Annual ACM Symposium on Applied Computing. New York, NY, USA, ACM New York, 1314-1319.

Preview

PDF Andrews_conceptual_approach.pdf - Accepted Version Creative Commons Attribution Non-commercial No Derivatives. Download (764kB) | Preview

Abstract

The analysis of gene expression data is a complex task for biologists wishing to understand the role of genes in the formation of diseases such as cancer. Biologists need greater support when trying to discover, and comprehend, new relationships within their data. In this paper, we describe an approach to the analysis of gene expression data where overlapping groupings are generated by Formal Concept Analysis and interactively analyzed in a tool called CUBIST. The CUBIST workflow involves querying a semantic database and converting the result into a formal context, which can be simplified to make it manageable, before it is visualized as a concept lattice and associated charts.

Item Type:	Book Section
Research Institute, Centre or Group - Does NOT include content added after October 2018:	Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Departments - Does NOT include content added after October 2018:	Faculty of Science, Technology and Arts > Department of Computing
Page Range:	1314-1319
Depositing User:	Simon Andrews
Date Deposited:	16 Jul 2013 13:37
Last Modified:	18 Mar 2021 14:06
URI:	https://shura.shu.ac.uk/id/eprint/7158

Actions (login required)

View Item

Downloads

Publication Metrics