Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 최성경 | - |
dc.date.accessioned | 2022-11-28T00:35:00Z | - |
dc.date.available | 2022-11-28T00:35:00Z | - |
dc.date.issued | 2019-11 | - |
dc.identifier.citation | Genes, v. 10.0, NO. 11, article no. 931, Page. 1-17 | en_US |
dc.identifier.issn | 2073-4425 | en_US |
dc.identifier.uri | https://www.mdpi.com/2073-4425/10/11/931 | en_US |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/177479 | - |
dc.description.abstract | Although there have been several analyses for identifying cancer-associated pathways, based on gene expression data, most of these are based on single pathway analyses, and thus do not consider correlations between pathways. In this paper, we propose a hierarchical structural component model for pathway analysis of gene expression data (HisCoM-PAGE), which accounts for the hierarchical structure of genes and pathways, as well as the correlations among pathways. Specifically, HisCoM-PAGE focuses on the survival phenotype and identifies its associated pathways. Moreover, its application to real biological data analysis of pancreatic cancer data demonstrated that HisCoM-PAGE could successfully identify pathways associated with pancreatic cancer prognosis. Simulation studies comparing the performance of HisCoM-PAGE with other competing methods such as Gene Set Enrichment Analysis (GSEA), Global Test, and Wald-type Test showed HisCoM-PAGE to have the highest power to detect causal pathways in most simulation scenarios. | en_US |
dc.description.sponsorship | This research was supported by the Bio-Synergy Research Project (2013M3A9C4078158) of the Ministry of Science, ICT and Future Planning through the National Research Foundation and by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI16C2037). The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. | en_US |
dc.language | en | en_US |
dc.publisher | Multidisciplinary Digital Publishing Institute (MDPI) | en_US |
dc.subject | pathway analysis | en_US |
dc.subject | survival phenotype | en_US |
dc.subject | Hierarchical structured component model | en_US |
dc.title | HisCoM-PAGE: Hierarchical Structural Component Models for Pathway Analysis of Gene Expression Data | en_US |
dc.type | Article | en_US |
dc.relation.no | 11 | - |
dc.relation.volume | 10.0 | - |
dc.identifier.doi | 10.3390/genes10110931 | en_US |
dc.relation.page | 1-17 | - |
dc.relation.journal | Genes | - |
dc.contributor.googleauthor | Mok, Lydia | - |
dc.contributor.googleauthor | Kim, Yongkang | - |
dc.contributor.googleauthor | Lee, Sungyoung | - |
dc.contributor.googleauthor | Choi, Sungkyoung | - |
dc.contributor.googleauthor | Lee, Seungyeoun | - |
dc.contributor.googleauthor | Jang, Jin-Young | - |
dc.contributor.googleauthor | Park, Taesung | - |
dc.sector.campus | E | - |
dc.sector.daehak | 과학기술융합대학 | - |
dc.sector.department | 응용수학과 | - |
dc.identifier.pid | day0413 | - |
dc.identifier.article | 931 | - |
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