김선 교수
Sun Kim
서울대학교 · 생화학·유전·분자생물학
연구실 소개
김선 교수의 연구실은 생물의학적 데이터, 특히 에피제네틱스와 유전자 발현의 상호작용을 중심으로 암의 치료 내성 메커니즘을 규명하고 있습니다. 특히 난소암의 플라티넘 저항성 발달 과정에서의 DNA 메틸화 변화와 관련된 전사적 억제 메커니즘을 분석하며, 새로운 치료 타겟과 생물학적 마커를 도출하고자 합니다. 또한, 의료 텍스트에서 약물 상호작용을 자동으로 추출하고, 저자 이름의 다의어 문제를 해결하기 위한 자연어 처리 및 기계학습 기반의 정보 검색 기술 개발에도 주력하고 있습니다. 이는 약물 부작용 조기 경고 및 정확한 문헌 검색 경험 향상에 기여합니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15Selective epigenetic disruption of distinct biological pathways was observed during development of platinum resistance in ovarian cancer. Integrated analysis of DNA methylation and gene expression may allow for the identification of new therapeutic targets and/or biomarkers prognostic of disease response. Finally, our results suggest that epigenetic therapies may facilitate the prevention or reversal of transcriptional repression responsible for chemoresistance and the restoration of sensitivity
Identifying unknown drug interactions is of great benefit in the early detection of adverse drug reactions. Despite existence of several resources for drug-drug interaction (DDI) information, the wealth of such information is buried in a body of unstructured medical text which is growing exponentially. This calls for developing text mining techniques for identifying DDIs. The state-of-the-art DDI extraction methods use Support Vector Machines (SVMs) with non-linear composite kernels to explore d
Log analysis shows that PubMed users frequently use author names in queries for retrieving scientific literature. However, author name ambiguity may lead to irrelevant retrieval results. To improve the PubMed user experience with author name queries, we designed an author name disambiguation system consisting of similarity estimation and agglomerative clustering. A machine-learning method was employed to score the features for disambiguating a pair of papers with ambiguous names. These features
Arylamine N-acetyltransferase type 1 (NAT1) is reported to be involved in the transfer of an acetyl group from acetyl-CoA to the terminal nitrogen of hydrazine and arylamine drugs or carcinogens. Gene-specific hypomethylation frequently occurs in a range of cancers and hypomethylation of the genes often correlates well with increased transcription levels. This study was conducted in order to evaluate the methylation status and the transcriptional activity of NAT1 in breast cancer tissues (n=72),
Supplementary data are available at Bioinformatics online.
Frailty was found to be correlated with cognitive impairment in non-demented older Koreans. However, further cohort studies are required to determine the association between frailty and cognitive function.
http://www.ncbi.nlm.nih.gov/IRET/PIE/.
BioC is a simple XML format for text, annotations and relations, and was developed to achieve interoperability for biomedical text processing. Following the success of BioC in BioCreative IV, the BioCreative V BioC track addressed a collaborative task to build an assistant system for BioGRID curation. In this paper, we describe the framework of the collaborative BioC task and discuss our findings based on the user survey. This track consisted of eight subtasks including gene/protein/organism nam
In this paper, we first discuss issues in clustering biological sequences with graph properties, which inspired the design of our sequence clustering algorithm BAG. BAG recursively utilises several graph properties: biconnectedness, articulation points, pquasi-completeness, and domain knowledge specific to biological sequence clustering. To reduce the fragmentation issue, we have developed a new metric called cluster utility to guide cluster splitting. Clusters are then merged back with less str
Even though problems still remain, utilizing syntactic information for article-level filtering helps improve PPI ranking performance. The proposed system is a revision of previously developed algorithms in our group for the ACT evaluation. Our approach is valuable in showing how to use grammatical relations for PPI article filtering, in particular, with a limited training corpus. While current performance is far from satisfactory as an annotation tool, it is already useful for a PPI article sear
Overall, we have found that grouping students according to their varying learning styles can be very useful for specific and various learning outcomes.
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