Exploiting scientific workflows for large-scale gene expression data analysis

Alessandro De Stasio, Marcus Ertelt, Wolfgang Kemmner, Ulf Leser, Michele Ceccarelli

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

1 Citation (Scopus)

Abstract

Microarrays are state technologies of the art for the measurement of expression of thousands of genes in a single experiment. The treatment of these data are typically performed with a wide range of tools, but the understanding of complex biological system by means of gene expression usually requires integrating different types of data from multiple sources and different services and tools. Many efforts are being developed on the new area of scientific workflows in order to create a technology that links both data and tools to create workflows that can easily be used by researchers. Currently technologies in this area aren't mature yet, making arduous the use of these technologies by the researcher. In this paper we present an architecture that helps the researchers to make large-scale gene expression data analysis with cutting edge technologies. The main underlying idea is to automate and rearrange the activities involved in gene expression data analysis, in order to freeing the user of superfluous technological details and tedious and errorprone tasks.

Original languageEnglish
Title of host publication2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009
Pages448-453
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2009
Externally publishedYes
Event2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009 - Guzelyurt, Cyprus
Duration: 14 Sep 200916 Sep 2009

Other

Other2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009
CountryCyprus
CityGuzelyurt
Period14/9/0916/9/09

Fingerprint

Gene expression
Biological systems
Microarrays
Genes
Experiments

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

De Stasio, A., Ertelt, M., Kemmner, W., Leser, U., & Ceccarelli, M. (2009). Exploiting scientific workflows for large-scale gene expression data analysis. In 2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009 (pp. 448-453). [5291850] https://doi.org/10.1109/ISCIS.2009.5291850

Exploiting scientific workflows for large-scale gene expression data analysis. / De Stasio, Alessandro; Ertelt, Marcus; Kemmner, Wolfgang; Leser, Ulf; Ceccarelli, Michele.

2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009. 2009. p. 448-453 5291850.

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

De Stasio, A, Ertelt, M, Kemmner, W, Leser, U & Ceccarelli, M 2009, Exploiting scientific workflows for large-scale gene expression data analysis. in 2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009., 5291850, pp. 448-453, 2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009, Guzelyurt, Cyprus, 14/9/09. https://doi.org/10.1109/ISCIS.2009.5291850
De Stasio A, Ertelt M, Kemmner W, Leser U, Ceccarelli M. Exploiting scientific workflows for large-scale gene expression data analysis. In 2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009. 2009. p. 448-453. 5291850 https://doi.org/10.1109/ISCIS.2009.5291850
De Stasio, Alessandro ; Ertelt, Marcus ; Kemmner, Wolfgang ; Leser, Ulf ; Ceccarelli, Michele. / Exploiting scientific workflows for large-scale gene expression data analysis. 2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009. 2009. pp. 448-453
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