Combinational logic network for digitally coded gene expression of gastric cancer
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, S. | - |
dc.contributor.author | Nam, S. | - |
dc.date.available | 2020-02-27T20:42:10Z | - |
dc.date.created | 2020-02-12 | - |
dc.date.issued | 2017 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/6635 | - |
dc.description.abstract | In general, Boolean networks have been addressed in time-series datasets. However, in the recent field of next-generation sequencing-based cancer genomics, cross-sectional data sets having enormous numbers of patients have been accumulated. Here, we deal with representation of cross-sectional datasets using Boolean networks, and specifically, combinational logic network approach. We then applied the approach to a real cancer patient dataset, demonstrating the feasibility of using Boolean networks in graphical representation of cross-sectional datasets. © 2016 IEEE. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.relation.isPartOf | Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 | - |
dc.subject | Bioinformatics | - |
dc.subject | Diseases | - |
dc.subject | Gene expression | - |
dc.subject | Boolean model | - |
dc.subject | Boolean Networks | - |
dc.subject | Cancer | - |
dc.subject | Combinational logic | - |
dc.subject | Graphical representations | - |
dc.subject | Logical network | - |
dc.subject | Network models | - |
dc.subject | Next-generation sequencing | - |
dc.subject | Computer circuits | - |
dc.title | Combinational logic network for digitally coded gene expression of gastric cancer | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.doi | 10.1109/BIBM.2016.7822788 | - |
dc.identifier.bibliographicCitation | Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016, pp.1777 - 1782 | - |
dc.identifier.scopusid | 2-s2.0-85013272379 | - |
dc.citation.endPage | 1782 | - |
dc.citation.startPage | 1777 | - |
dc.citation.title | Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 | - |
dc.contributor.affiliatedAuthor | Park, S. | - |
dc.contributor.affiliatedAuthor | Nam, S. | - |
dc.type.docType | Conference Paper | - |
dc.subject.keywordAuthor | Boolean models | - |
dc.subject.keywordAuthor | Cancer | - |
dc.subject.keywordAuthor | Logical networks | - |
dc.subject.keywordAuthor | Network models | - |
dc.subject.keywordPlus | Bioinformatics | - |
dc.subject.keywordPlus | Diseases | - |
dc.subject.keywordPlus | Gene expression | - |
dc.subject.keywordPlus | Boolean model | - |
dc.subject.keywordPlus | Boolean Networks | - |
dc.subject.keywordPlus | Cancer | - |
dc.subject.keywordPlus | Combinational logic | - |
dc.subject.keywordPlus | Graphical representations | - |
dc.subject.keywordPlus | Logical network | - |
dc.subject.keywordPlus | Network models | - |
dc.subject.keywordPlus | Next-generation sequencing | - |
dc.subject.keywordPlus | Computer circuits | - |
dc.description.journalRegisteredClass | scopus | - |
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