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Identification of gene modules using a generative model for relational data Lacerda, Gustavo
Abstract
This thesis presents generative models for two types of relational data (edge rankings and networks) from block structures, based on Brumm et al (2008). We design and implement a set of inference algorithms, and evaluate them on real as well as simulated data. We conclude with a discussion of how well the real data fits the model, and with various extensions of the basic model.
Item Metadata
| Title |
Identification of gene modules using a generative model for relational data
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| Creator | |
| Publisher |
University of British Columbia
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| Date Issued |
2010
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| Description |
This thesis presents generative models for two types of relational data (edge rankings and networks) from block structures, based on Brumm et al (2008). We design and implement a set of inference algorithms, and evaluate them on real as
well as simulated data. We conclude with a discussion of how well the real data fits the model, and with various extensions of the basic model.
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| Genre | |
| Type | |
| Language |
eng
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| Date Available |
2010-08-30
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| Provider |
Vancouver : University of British Columbia Library
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| Rights |
Attribution-NonCommercial-ShareAlike 3.0 Unported
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| DOI |
10.14288/1.0051953
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| URI | |
| Degree | |
| Program | |
| Affiliation | |
| Degree Grantor |
University of British Columbia
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| Graduation Date |
2010-11
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| Campus | |
| Scholarly Level |
Graduate
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| Rights URI | |
| Aggregated Source Repository |
DSpace
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Item Media
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Rights
Attribution-NonCommercial-ShareAlike 3.0 Unported