NCBI logo Computational Biology Branch
PubMed Entrez BLAST OMIM Books TaxBrowser Structure

NCBI
back to NCBI homepage
back to NCBI homepage
SITE MAP

Seminar schedule

Postdoctoral fellow's Web pages

Senior Investigators in PubMed

BACK

spacer gif

Sun Kim
Postdoctoral Fellow
Computational Biology Branch
National Center for Biotechnology Information (NCBI)
National Institutes of Health (NIH)
Bethesda, MD 20894

Tel: 301-496-2484
E-mail: sun.kim at nih.gov, skim at bi.snu.ac.kr
Personal page: http://echosf.net
Short Bio
Sun Kim is a Postdoctoral Fellow at the National Center for Biotechnology Information (NCBI), where he joined right after receiving his PhD degree in Computer Science and Engineering from Seoul National University in 2009. His research interests include:

  • Text mining
  • Bioinformatics
  • Molecular evolutionary learning of hypernetworks
  • Kernel methods
  • Evolutionary algorithms
Journal Publications
  • Ensembled Support Vector Machines for Human Papillomavirus Risk Type Prediction from Protein Secondary Structures, S. Kim, J. Kim, and B.-T. Zhang, Computers in Biology and Medicine, 39(2), pp. 187-193, 2009.
  • Introducing Meta-Services for Biomedical Information Extraction, F. Leitner, M. Krallinger, C. Rodriguez-Penagos, J. Hakenberg, C. Plake, C.-J. Kuo, C.-N. Hsu, R. T. Tasi, H.-C. Hung, W. W. lau, C. A. Johnson, R. Satre, K. Yoshida, Y. H. Chen, S. Kim, S.-Y. Shin, B.-T. Zhang, W. A. Baumgartner, Jr., L. Hunter, B. Haddow, M. Matthews, X. Wang, P. Ruch, F. Ehrler, A. Ozgur, G. Erkan, D. R. Radev, M. Krauthammer, T. Luong, R. Hoffmann, C. Sander, and A. Valencia, Genome Biology, 9(Suppl 2), S6, 2008.
  • PIE: an online prediction system for protein-protein interactions from text, S. Kim*, S.-Y. Shin*, I.-H. Lee, S.-J. Kim, R. Sriram, and B.-T. Zhang, Nucleic Acids Research, 36, W411-W415, 2008.
  • Human Papillomavirus Risk Type Classification from Protein Sequences Using Support Vector Machines, S. Kim and B.-T. Zhang, Lecture Notes in Computer Science (EVOBIO 2006), 3907, pp. 57-66, 2006.
  • Multi-objective Evolutionary Probe Design Based on Thermodynamic Criteria for HPV Detection, I.-H. Lee, S. Kim, and B.-T. Zhang, Lecture Notes in Artificial Intelligence (PRICAI 2004), 3157, pp. 742-750, 2004.
  • Genetic Mining of HTML Structures for Effective Web-Document Retrieval, S. Kim and B.-T. Zhang, Applied Intelligence, 18(3), pp. 243-256, 2003.
Conference Publications
  • Evolutionary Hypernetwork Classifiers for Protein-Protein Interaction Sentence Filtering, J. Bootkrajang, S. Kim, and B.-T. Zhang, Genetic and Evolutionary Computation Conference (GECCO 2009), pp. 185-192, 2009.
  • Evolving Hypernetwork Models of Binary Time Series for Forecasting Price Movements on Stock Markets, E. Bautu, S. Kim, A. Bautu, H. Luchian, and B.-T. Zhang, IEEE Congress on Evolutionary Computation (CEC 2009), pp. 166-173, 2009.
  • Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm, C.-H. Park*, S.-J. Kim*, S. Kim, D.-Y. Cho, and B.-T. Zhang, IEEE International Symposium on Bioinformatics and Biomedical Engineering (BIBE 2007), pp. 158-163, 2007.
  • Evolving Hypernetwork Classifiers for microRNA Expression Profile Analysis, S. Kim*, S.-J. Kim*, and B.-T. Zhang, IEEE Congress on Evolutionary Computation (CEC 2007), pp. 313-319, 2007.
  • Use of Evolutionary Hypernetworks for Mining Prostate Cancer Data, C.-H. Park*, S.-J. Kim*, S. Kim, D.-Y. Cho, and B.-T. Zhang, International Symposium on Advanced Intelligent Systems, pp. 702-706, 2007.
  • Identifying Protein-Protein Interaction Sentences Using Boosting and Kernel Methods, S.-Y. Shin*, S. Kim*, J.-H. Eom, B.-T. Zhang, and R. Sriram, Second BioCreative Challenge Workshop, pp. 187-192, 2007.
  • Text Classifiers Evolved on a Simulated DNA Computer, S. Kim, M.-O. Heo, and B.-T. Zhang, IEEE Congress on Evolutionary Computation (CEC 2006), pp. 9196-9202, 2006.
  • A Tree Kernel-Based Method for Protein-Protein Interaction Mining from Biomedical Literature, J.-H. Eom, S. Kim, S.-H. Kim, and B.-T. Zhang, Lecture Notes in Bioinformatics (KDLL 2006), 3886, pp. 42-52, 2006.
  • Evolutionary Learning of Web-Document Structure for Information Retrieval, S. Kim and B.-T. Zhang, IEEE Congress on Evolutionary Computation (CEC 2001), pp. 1253-1260, 2001.
  • SCAI Experiments on TREC-9, Y.-H. Kim, S. Kim, J.-H. Eom, and B.-T. Zhang, Text Retrieval Conference (TREC-9), pp. 392-399, 2000.
  • Web-Document Retrieval by Genetic Learning of Importance Factors for HTML Tags, S. Kim and B.-T. Zhang, PRICAI 2000 Workshop on Text and Web Mining, pp. 13-23, 2000.
  • SCAI TREC-8 Experiments, D.-H. Shin, Y.-H. Kim, S. Kim, J.-H. Eom, H.-J. Shin, and B.-T. Zhang, Text Retrieval Conference (TREC-8), pp. 511-518, 1999.
Book Chapters
  • Natural Language Processing, Y.-T. Kim et al., 2001 (in Korean).
Korean Publications
  • 하이퍼네트워크 모델을 이용한 텍스트 문장 분류, 작가멧, 김선, 장병탁, 대한전자공학회 추계학술대회 논문집, 31(2), pp. 987-988, 2008.
  • 기계번역문장 품질 평가를 위한 하이퍼네트워크 기반 언어 모델링, 고영길, 장하영, 김선, 장병탁, 정보통신분야학회 합동학술대회 논문집, pp. 277-280, 2008.
  • 마이크로어레이 기반 miRNA 모듈 분석을 위한 하이퍼망 분류 기법, 김선, 김수진, 장병탁, 정보과학회논문지 : 소프트웨어 및 응용, 35(6), pp. 347-356, 2008.
  • DNA Chip Informatics 기술, 장병탁, 황규백, 정제균, 김선, 엄재홍, 바이오웹진, 2003.
  • 다수의 목표 유전자에서 진화연산을 이용한 Oligonucleotide Probe 선택, 신기루, 김선, 장병탁, 한국정보과학회 봄 학술발표 논문집, 30(1), pp. 455-457, 2003.
  • Oligonucleotide Microarray의 Probe 선택을 위한 진화적인 접근 방법, 김선, 장병탁, 한국데이터마이닝학회 추계학술대회 논문집, pp. 140-147, 2002.
  • 유전 알고리즘을 이용한 DNA Microarray의 Probe 선택, 김선, 장병탁, 한국퍼지 및 지능시스템학회 춘계 학술발표 논문집, pp. 183-186, 2002.
  • 진화연산을 이용한 웹 문서의 특성 학습, 김선, 장병탁, 한국퍼지 및 지능시스템학회 춘계 학술발표 논문집, pp. 43-46, 2000.
Invited Talks
  • DNAChipBench: Integrated DNA-Chip Informatics Platform, ICT-Asia Seminar, French Ministry of Foreign and European Affairs, Taipei, Nov. 20, 2007.
  • 진화연산 기반의 웹 문서 검색방법, 서울디지털산업단지 기술장터, Seoul Industry Academia Forum and Seoul National University Industry Foundation, Seoul, Jun. 14, 2007.
Publications in Google Scholar

Disclaimer     Privacy statement

Revised: August 5, 2009.