Nak-Kyeong Kim

Ph.D. in Statistics, Purdue University, (2005)

M.S. in Statistics, Purdue University, (2001)

B.S. in Computer Science and Statistics, Seoul National University, (1999)

B.S. in Computer Science and Statistics, Seoul National University, (1999)

Research Interests

Statistics in Bioinformatics, Bayesian modeling and Markov chain Monte Carlo methods, Transcription factor binding sites identification in DNA sequence, Protein motif identification, ChIP-chip and ChIP-Seq data analysis

Articles

Kim, N., Tharakaraman, K., Marino-Ramirez, L. and Spouge, J. L.. (2008). Finding sequence motifs with Bayesian models incorporating positional information: an application to predicting transcription factor binding sites. BMC Bioinformatics 9 (262).

Kim, N., Tharakaraman, K. and Spouge, J. L.. (2006). Adding sequence context to a Markov background model improves the identification of regulatory elements. Bioinformatics 22 (23) , pp. 2870-2875.

Kim, N. and Xie, J. (2006). Protein Multiple Alignment Incorporating Primary and Secondary Structure. Journal of Computational Biology 13 (9) , pp. 1615-1629.

Xie, J. and Kim, N. (2005). Bayesian Models and Markov Chain Monte Carlo Methods with the Secondary Characteristics. Journal of Computational Biology 12 (7) , pp. 952-970.

Presentations

Kim, N. (August , 2009). Finding sequence motifs with Bayesian models incorporating positional information 2009 Annual Meeting of American Statistical Association .

Kim, N. (July , 2009). Finding sequence motifs with Bayesian models incorporating positional information Twelfth Meeting of New Researchers in Statistics and Probability Baltimore.

Kim, N. (May , 2009). Sequence motif identification incorporating extra information 2009 Annual Meeting of Virginia Academy of Sciences Statistical section Richmond, Virginia.

Kim, N. (January , 2009). Improving biological sequence alignments Math/Stat Club Meeting Norfolk, VA.

Kim, N. (July , 2007). Protein Multiple Alignment Using Primary and Secondary Structure Information 2007 Annual Meeting of American Statistical Association Salt Lake City, Utah.

Kim, N. (May , 2007). Finding motifs with Bayesian models combining sequence and positional information Computational Biology Branch Seminar Bethesda, Maryland.

Kim, N. (March , 2007). Improving Motif Identification in Biological Sequences Statistics Colloquium Baltimore County, Maryland.

Kim, N. (June , 2005). A Statistical Method of Identifying Protein Motifs by Combining Amino Acid Sequence and Secondary Structures 2005 Annual Meeting of Intelligent Systems for Molecular Biology (ISMB) Detroit, Michigan.

Kim, N. (May , 2004). Bayesian Models and Markov Chain Monte Carlo Methods for Protein Motifs with the Secondary Characteristics First Annual Indiana Bioinformatics Conference .

• Postdoctoral Visiting Fellowship, NIH
• Scholarships, Seoul National University
• 2005: ISMB travel followship, International Society for Computational Biology (ISBC)