Use of data-biased random walks on graphs for the retrieval of context-specific networks from genomic data.
Extracting network-based functional relationships within genomic datasets is an important challenge in the computational analysis of large-scale data. Although many methods, both public and commercial, have been developed, the problem of identifying networks of interactions that are most relevant to...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2010-08-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20808879/pdf/?tool=EBI |
| _version_ | 1818211389297131520 |
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| author | Kakajan Komurov Michael A White Prahlad T Ram |
| author_facet | Kakajan Komurov Michael A White Prahlad T Ram |
| author_sort | Kakajan Komurov |
| collection | DOAJ |
| description | Extracting network-based functional relationships within genomic datasets is an important challenge in the computational analysis of large-scale data. Although many methods, both public and commercial, have been developed, the problem of identifying networks of interactions that are most relevant to the given input data still remains an open issue. Here, we have leveraged the method of random walks on graphs as a powerful platform for scoring network components based on simultaneous assessment of the experimental data as well as local network connectivity. Using this method, NetWalk, we can calculate distribution of Edge Flux values associated with each interaction in the network, which reflects the relevance of interactions based on the experimental data. We show that network-based analyses of genomic data are simpler and more accurate using NetWalk than with some of the currently employed methods. We also present NetWalk analysis of microarray gene expression data from MCF7 cells exposed to different doses of doxorubicin, which reveals a switch-like pattern in the p53 regulated network in cell cycle arrest and apoptosis. Our analyses demonstrate the use of NetWalk as a valuable tool in generating high-confidence hypotheses from high-content genomic data. |
| first_indexed | 2024-12-12T05:31:43Z |
| format | Article |
| id | doaj.art-70f9f1b749904e2ab617cbcc68214f84 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-12T05:31:43Z |
| publishDate | 2010-08-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-70f9f1b749904e2ab617cbcc68214f842022-12-22T00:36:17ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582010-08-0168e100088910.1371/journal.pcbi.1000889Use of data-biased random walks on graphs for the retrieval of context-specific networks from genomic data. Kakajan KomurovMichael A WhitePrahlad T RamExtracting network-based functional relationships within genomic datasets is an important challenge in the computational analysis of large-scale data. Although many methods, both public and commercial, have been developed, the problem of identifying networks of interactions that are most relevant to the given input data still remains an open issue. Here, we have leveraged the method of random walks on graphs as a powerful platform for scoring network components based on simultaneous assessment of the experimental data as well as local network connectivity. Using this method, NetWalk, we can calculate distribution of Edge Flux values associated with each interaction in the network, which reflects the relevance of interactions based on the experimental data. We show that network-based analyses of genomic data are simpler and more accurate using NetWalk than with some of the currently employed methods. We also present NetWalk analysis of microarray gene expression data from MCF7 cells exposed to different doses of doxorubicin, which reveals a switch-like pattern in the p53 regulated network in cell cycle arrest and apoptosis. Our analyses demonstrate the use of NetWalk as a valuable tool in generating high-confidence hypotheses from high-content genomic data.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20808879/pdf/?tool=EBI |
| spellingShingle | Kakajan Komurov Michael A White Prahlad T Ram Use of data-biased random walks on graphs for the retrieval of context-specific networks from genomic data. PLoS Computational Biology |
| title | Use of data-biased random walks on graphs for the retrieval of context-specific networks from genomic data. |
| title_full | Use of data-biased random walks on graphs for the retrieval of context-specific networks from genomic data. |
| title_fullStr | Use of data-biased random walks on graphs for the retrieval of context-specific networks from genomic data. |
| title_full_unstemmed | Use of data-biased random walks on graphs for the retrieval of context-specific networks from genomic data. |
| title_short | Use of data-biased random walks on graphs for the retrieval of context-specific networks from genomic data. |
| title_sort | use of data biased random walks on graphs for the retrieval of context specific networks from genomic data |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20808879/pdf/?tool=EBI |
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