Robust cross-race gene expression analysis
This paper develops a Bayesian network (BN) predictor to profile cross-race gene expression data. Cross-race studies face more data variability than single-lab studies. Our design handles this problem by using the BN framework. In addition, unlike existing methods that unrealistically assume ind...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers
2010
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| Online Access: | http://hdl.handle.net/1721.1/58098 |
| _version_ | 1826211873977008128 |
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| author | Ramoni, Marco F. Chang, Hsun-Hsien |
| author2 | Harvard University--MIT Division of Health Sciences and Technology |
| author_facet | Harvard University--MIT Division of Health Sciences and Technology Ramoni, Marco F. Chang, Hsun-Hsien |
| author_sort | Ramoni, Marco F. |
| collection | MIT |
| description | This paper develops a Bayesian network (BN) predictor to profile
cross-race gene expression data. Cross-race studies face more data
variability than single-lab studies. Our design handles this problem
by using the BN framework. In addition, unlike existing methods
that unrealistically assume independent genes, our BN approach can
capture the dependencies among genes. Existing BN algorithms in
biomedicine applications quantize data, leading to information loss;
we adopt linear Gaussian model to keep the data intact, so our resulting
model is more reliable. The application of our BN predictor to a
lung adenocarcinoma study shows high prediction accuracy, and performance
evaluation demonstrates our gene signature agreeable with
those reported in the literature. Our tool has a promising potential in
finding disease biomarkers common to multiple races. |
| first_indexed | 2024-09-23T15:12:46Z |
| format | Article |
| id | mit-1721.1/58098 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:12:46Z |
| publishDate | 2010 |
| publisher | Institute of Electrical and Electronics Engineers |
| record_format | dspace |
| spelling | mit-1721.1/580982022-09-29T13:23:56Z Robust cross-race gene expression analysis Ramoni, Marco F. Chang, Hsun-Hsien Harvard University--MIT Division of Health Sciences and Technology Ramoni, Marco F. Ramoni, Marco F. This paper develops a Bayesian network (BN) predictor to profile cross-race gene expression data. Cross-race studies face more data variability than single-lab studies. Our design handles this problem by using the BN framework. In addition, unlike existing methods that unrealistically assume independent genes, our BN approach can capture the dependencies among genes. Existing BN algorithms in biomedicine applications quantize data, leading to information loss; we adopt linear Gaussian model to keep the data intact, so our resulting model is more reliable. The application of our BN predictor to a lung adenocarcinoma study shows high prediction accuracy, and performance evaluation demonstrates our gene signature agreeable with those reported in the literature. Our tool has a promising potential in finding disease biomarkers common to multiple races. National Institutes of Health (U.S.) (NIH/NHGRI R01HG003354) 2010-09-01T18:59:23Z 2010-09-01T18:59:23Z 2009-01 Article http://purl.org/eprint/type/ConferencePaper 9781424423538 1520-6149 http://hdl.handle.net/1721.1/58098 Chang, Hsun-Hsien and M.F. Ramoni. "Robust cross-race gene expression analysis," Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on, pp.505-508, 19-24 (April 2009) © 2009 Institute of Electrical and Electronics Engineers. en_US http://dx.doi.org/10.1109/ICASSP.2009.4959631 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2009 Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Institute of Electrical and Electronics Engineers IEEE |
| spellingShingle | Ramoni, Marco F. Chang, Hsun-Hsien Robust cross-race gene expression analysis |
| title | Robust cross-race gene expression analysis |
| title_full | Robust cross-race gene expression analysis |
| title_fullStr | Robust cross-race gene expression analysis |
| title_full_unstemmed | Robust cross-race gene expression analysis |
| title_short | Robust cross-race gene expression analysis |
| title_sort | robust cross race gene expression analysis |
| url | http://hdl.handle.net/1721.1/58098 |
| work_keys_str_mv | AT ramonimarcof robustcrossracegeneexpressionanalysis AT changhsunhsien robustcrossracegeneexpressionanalysis |