DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Lee, Doheon | - |
dc.contributor.advisor | 이도헌 | - |
dc.contributor.author | Lee, Saehwan | - |
dc.date.accessioned | 2019-09-03T02:41:02Z | - |
dc.date.available | 2019-09-03T02:41:02Z | - |
dc.date.issued | 2019 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=843109&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/266178 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 바이오및뇌공학과, 2019.2,[iv, 51 p. :] | - |
dc.description.abstract | Drug effect prediction requires understanding of protein functions and interactions, and protein interactions are affected by cell types and post-translational modification, namely phosphorylation. A specific post-translationally modified form of protein product is called a proteoform and should be distinguished from other proteoforms arising from the same protein. A cell line-specific and retinoic acid treatment-specific protein-protein interaction network was constructed by integrating the traditional protein-protein interaction information and proteoform information and experimental transcriptome and phosphoproteome profiles for two breast cancer cell lines MCF-7 (retinoic acid-sensitive) and BT-474 (retinoic acid-resistant) each before and after treatment. The effect of retinoic acid was computed from measuring the shortest path length from the drug targets to the sample-specific network comparing the length before and after the treatment. Despite the lack of statistical significance, the decrease of the average shortest path length to MCF-7-specific proteins may reflect the sample-specific proteins to be affected in favor of retinoic acid treatment compared to that of BT-474-specific proteins. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | post-translational modification▼aphosphoprotein▼aprotein-protein interaction▼anetwork biology▼adrug effect prediction | - |
dc.subject | 전사 후 수정▼a인산화단백질▼a단백질 상호작용▼a네트워크 생물학▼a약물 효과 예측 | - |
dc.title | Drug effect prediction based on phosphoprotein interactions | - |
dc.title.alternative | 인산화단백질 상호작용 기반 약물 효과 예측 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :바이오및뇌공학과, | - |
dc.contributor.alternativeauthor | 이세환 | - |
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