AGRA: Analysis of gene ranking algorithms

Kocbek, S, Sætre, R, Stiglic, G, Kim, J, Pernek, I, Tsuruoka, Y, Kokol, P, Ananiadou, S and Tsujii, J 2011, 'AGRA: Analysis of gene ranking algorithms', Bioinformatics, vol. 27, no. 8, pp. 1185-1186.


Document type: Journal Article
Collection: Journal Articles

Title AGRA: Analysis of gene ranking algorithms
Author(s) Kocbek, S
Sætre, R
Stiglic, G
Kim, J
Pernek, I
Tsuruoka, Y
Kokol, P
Ananiadou, S
Tsujii, J
Year 2011
Journal name Bioinformatics
Volume number 27
Issue number 8
Start page 1185
End page 1186
Total pages 2
Publisher Oxford University Press
Abstract Often, the most informative genes have to be selected from different gene sets and several computer gene ranking algorithms have been developed to cope with the problem. To help researchers decide which algorithm to use, we developed the analysis of gene ranking algorithms (AGRA) system that offers a novel technique for comparing ranked lists of genes. The most important feature of AGRA is that no previous knowledge of gene ranking algorithms is needed for their comparison. Using the text mining system finding-associated concepts with text analysis. AGRA defines what we call biomedical concept space (BCS) for each gene list and offers a comparison of the gene lists in six different BCS categories. The uploaded gene lists can be compared using two different methods. In the first method, the overlap between each pair of two gene lists of BCSs is calculated. The second method offers a text field where a specific biomedical concept can be entered. AGRA searches for this concept in each gene lists' BCS, highlights the rank of the concept and offers a visual representation of concepts ranked above and below it.
Subject Mathematical Sciences not elsewhere classified
DOI - identifier 10.1093/bioinformatics/btr097
Copyright notice © The Author(s) 2011. Published by Oxford University Press
ISSN 1367-4803
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