A conceptual approach to gene expression analysis enhanced by visual analytics

Cassio Melo; Marie-aude Aufaure; Constantinos Orphanides; Simon Andrews; Kenneth Mcleod; Albert Burger

doi:10.1145/2480362.2480610

A conceptual approach to gene expression analysis enhanced by visual analytics

Cassio Melo, Marie-aude Aufaure, Constantinos Orphanides, Simon Andrews, Kenneth Mcleod, Albert Burger

Research output: Contribution to conference › Other › peer-review

3 Citations (Scopus)

18 Downloads (Pure)

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.

Original language	English
Pages	1314-1319
DOIs	https://doi.org/10.1145/2480362.2480610
Publication status	Published - 2013
Event	the 28th Annual ACM Symposium - Coimbra, Portugal, United Kingdom Duration: 18 Mar 2013 → 22 Mar 2013

Conference

Conference	the 28th Annual ACM Symposium
Country/Territory	United Kingdom
City	Coimbra, Portugal
Period	18/03/13 → 22/03/13

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1145/2480362.2480610

Cite this

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title = "A conceptual approach to gene expression analysis enhanced by visual analytics",

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.",

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note = "the 28th Annual ACM Symposium ; Conference date: 18-03-2013 Through 22-03-2013",

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AU - Melo, Cassio

AU - Aufaure, Marie-aude

AU - Orphanides, Constantinos

AU - Andrews, Simon

AU - Mcleod, Kenneth

AU - Burger, Albert

PY - 2013

Y1 - 2013

N2 - 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.

AB - 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.

U2 - 10.1145/2480362.2480610

DO - 10.1145/2480362.2480610

M3 - Other

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EP - 1319

T2 - the 28th Annual ACM Symposium

Y2 - 18 March 2013 through 22 March 2013

ER -

A conceptual approach to gene expression analysis enhanced by visual analytics

Abstract

Conference

UN SDGs

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Cite this