• Course Description
  
  • This course covers computational techniques for mining the large amount of information produced by recent advances in biology, such as genome sequencing and microarrray technologies. Main topics of the course include:
    • DNA and protein sequence alignment,
    • sequence motifs/patterns,
    • phylogenetic trees,
    • protein structures: prediction, alignment, classification
    • microarray data analysis: normalization, clustering
    • and biological networks.
  
  
• Lecture Time/Place
  
  • Mondays 9:40-11:30
  • Thursdays 12:40-13:30
  • First meeting on March 15, Monday at 9:40AM. The lectures will be online at my Cisco Webex Personal meeting room: https://metu.webex.com/meet/tcan.
  • NOTE: Note that this is a Technical Elective course. The capacity for TE courses are 0 during registration, because a departmental TE allocation system is used. I will collect a list of non-CENG/irregular students who want to take the course and these students will be able to add the course during add-drops.
  
  
  
• Reading Material
  
  • Textbook:
    • M. Zvelebil and J. O. Baum, Understanding Bioinformatics, Garland Science, 2008.
      
  • Reference Books:
    • D.E. Krane and M.L. Raymer, Fundamental Concepts of Bioinformatics, Pearson Education, 2003.
    • N. C. Jones and P. A. Pevzner, An Introduction to Bioinformatics Algorithms, MIT press, 2004.
    • C.A. Orengo, D.T. Jones and J.M.Thornton, Bioinformatics: Genes, Proteins and Computers, Roultledge, 2003.
    • A. M. Lesk, Introduction to Bioinformatics, Oxford University Press, 2002.
    • D. Mount, Bioinformatics: Sequence and genome analysis, Cold Spring Harbor Laboratory Press, 2001.
    • P. A. Pevzner, Computational Molecular Biology: An Algorithmic Approach, MIT press, 2000.
    • P. Baldi and S. Brunak, Bioinformatics: the machine learning approach (2nd edition), MIT press, 2001.
    • T. Jiang, Y. Xu, and M. Zhang, eds. Current Topics in Computational Molecular Biology, MIT press, 2002.
    • S. Karlin, Frontiers of Bioinformatics: Unsolved Problems and Challenges, National Academy Press, 2005
• Prerequisites
  
  • Programming. Algorithms.
• Goals
  
  • The main objective of the course is to provide the student with a solid foundation for conducting further research in bioinformatics. By the end of the course, the students will have learned:
    • the bioinformatics terminology,
    • main bioinformatics problems,
    • and the key methods and tools used in bioinformatics.
  
  

Tolga Can   (tcan@ceng.metu.edu.tr)
Office Location: Computer Engineering, B-109
Office Hours: by appointment

Hazal Mogultay