Bioinformatics Research Group at BI Lab

The Bioinformatics Research Group at the Biointelligence Lab is interested in developing and applying machine learning algorithms for the analysis of genomic and proteomic data with a specal emphasis on DNA chip data mining. Current research focuses on probabilistic graphical models, including hidden Markov models (HMMs), Bayesian networks, Helmholtz machines, latent variable models, and generative topographic mapping.

Upcoming Conferences on Bioinformatics 

 

Seminars

Tutorials

Invited Talks

Research Projects

  • SysBio: In silico modeling and network construction of chromosomal replication and segregation
  • BrainGene : DNA data mining for the analysis of expression patterns of vertebrate brain development-specific genes (rat)
  • AngioProt : Development of prediction algorithm for angiogenesis-related molecules
  • DMDM: DNA microarray data mining using unsupervised learning techniques
  • ProClass: Protein classification based on molecular sequence and text information
  • BioText: Information extraction from biological texts based on Markov models
  • MicroGene: Microbial gene identification using probabilistic graphical models

Useful Links

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This page is maintained by Je-Gun Joung (jgjoung@bi.snu.ac.kr).
Last update: April. 24, 2004.