Presentation | 2006-06-15 Predicting type of protein-protein interaction as a multiple-instance learning problem Hiroshi YAMAKAWA, Yoshio NAKAO, Koji MARUHASHI, |
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Abstract(in English) | We propose a method for predicting types of protein-protein interactions using a multiple-instance learning (MIL) model. By assuming cause of each interaction between proteins containing two or more subunit is results from local subunit pairs, we formulates this problem as MIL. In this problem, influences from instances in negative bag to target concepts are too strong by using well-known Maron's method. We propose a new MIL method based on decision by majority and apply to the KEGG interaction data. In an experiment using the KEGG pathways and the Gene Ontology, the method successfully predicted an interaction type (phosphorylation) at the accuracy rate of 86.1%. We find that cause of false positive is caused by positive bias peculiar to MIL method by analyzing prediction results. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | protein-protein interaction / multiple-instance learning / diverse density / phosphorylation / subunit |
Paper # | NC2006-15 |
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Committee | NC |
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Conference Date | 2006/6/8(1days) |
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Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Predicting type of protein-protein interaction as a multiple-instance learning problem |
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Keyword(1) | protein-protein interaction |
Keyword(2) | multiple-instance learning |
Keyword(3) | diverse density |
Keyword(4) | phosphorylation |
Keyword(5) | subunit |
1st Author's Name | Hiroshi YAMAKAWA |
1st Author's Affiliation | FUJITSU LABORATORIES LTD.() |
2nd Author's Name | Yoshio NAKAO |
2nd Author's Affiliation | FUJITSU LABORATORIES LTD. |
3rd Author's Name | Koji MARUHASHI |
3rd Author's Affiliation | FUJITSU LABORATORIES LTD. |
Date | 2006-06-15 |
Paper # | NC2006-15 |
Volume (vol) | vol.106 |
Number (no) | 101 |
Page | pp.pp.- |
#Pages | 6 |
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