| Title: | AGRA: analysis of gene ranking algorithms |
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| Authors: | ID Kocbek, Simon (Author)
ID Saetre, Rune (Author)
ID Štiglic, Gregor (Author)
ID Kim, Jin-Dong (Author)
ID Pernek, Igor (Author)
ID Tsuruoka, Yoshimasa (Author)
ID Kokol, Peter (Author)
ID Ananiadou, Sophia (Author)
ID Tsujii, Jun-ichi (Author) |
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| Files: |  http://bioinformatics.oxfordjournals.org/content/27/8/1185.full.pdf
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| Language: | English |
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| Work type: | Unknown |
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| Typology: | 1.03 - Other scientific articles |
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| Organization: | FZV - Faculty of Health Sciences
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| Abstract: | Often, the most informative genes have to be selected from different gene setsand 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 FACTA (Tsuruoka et al., 2008), AGRA defines what we call Biomedical Concept Space (BCS) for each gene list and offers 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 specific biomedical concept can be entered. AGRA searches for this concept in each genelistsć BCS, highlights the rank of the concept and offers a visual representation of concepts ranked above and below it. |
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| Keywords: | genetic algorithms, genetski algoritmi |
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| Year of publishing: | 2011 |
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| PID: | 20.500.12556/DKUM-30850  |
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| UDC: | 004.8:575 |
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| ISSN on article: | 1460-2059 |
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| COBISS.SI-ID: | 1676708 |
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| NUK URN: | URN:SI:UM:DK:Y6IUVJHB |
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| Publication date in DKUM: | 05.06.2012 |
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| Views: | 2492 |
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| Downloads: | 161 |
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| Metadata: |    |
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| Categories: | Misc.
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