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DC Field | Value | Language |
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dc.citation.endPage | 245 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 229 | - |
dc.citation.title | MACHINE LEARNING | - |
dc.citation.volume | 65 | - |
dc.contributor.author | Nam, Dougu | - |
dc.contributor.author | Seo, Seunghyun | - |
dc.contributor.author | Kim, Sangsoo | - |
dc.date.accessioned | 2023-12-22T09:41:47Z | - |
dc.date.available | 2023-12-22T09:41:47Z | - |
dc.date.created | 2014-10-13 | - |
dc.date.issued | 2006-10 | - |
dc.description.abstract | Boolean networks provide a simple and intuitive model for gene regulatory networks, but a critical defect is the time required to learn the networks. In recent years, efficient network search algorithms have been developed for a noise-free case and for a limited function class. In general, the conventional algorithm has the high time complexity of O(22k mn k+1) where m is the number of measurements, n is the number of nodes (genes), and k is the number of input parents. Here, we suggest a simple and new approach to Boolean networks, and provide a randomized network search algorithm with average time complexity O (mn k+1/ (log m)(k-1)). We show the efficiency of our algorithm via computational experiments, and present optimal parameters. Additionally, we provide tests for yeast expression data. | - |
dc.identifier.bibliographicCitation | MACHINE LEARNING, v.65, no.1, pp.229 - 245 | - |
dc.identifier.doi | 10.1007/s10994-006-9014-z | - |
dc.identifier.issn | 0885-6125 | - |
dc.identifier.scopusid | 2-s2.0-33749005690 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/7185 | - |
dc.identifier.url | http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=33749005690 | - |
dc.identifier.wosid | 000240797500008 | - |
dc.language | 영어 | - |
dc.publisher | SPRINGER | - |
dc.title | An efficient top-down search algorithm for learning Boolean networks of gene expression | - |
dc.type | Article | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | Boolean network | - |
dc.subject.keywordAuthor | data consistency | - |
dc.subject.keywordAuthor | random superset selection | - |
dc.subject.keywordAuthor | core search | - |
dc.subject.keywordAuthor | coupon collection problem | - |
dc.subject.keywordPlus | REGULATORY NETWORKS | - |
dc.subject.keywordPlus | MODEL | - |
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