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Biological Data Mining / Bioinformatics

Since the discovery of the structure of DNA (Watson & Crick, 1953), Molecular Biology has evolved rapidly, following the explosive rates of information technology, which has provided a wide range of tools and techniques for storing and analyzing biological data. Large scale data collection projects such as the “Human Genome Project” required powerful computational tools. For the past three decades, there is a strong interest in knowledge discovery methods, to generate models of biological systems. In order to build knowledge discovery systems that contribute to our understanding of biological systems, biological research requires efficient and scalable data mining systems.

One of the many applications of data mining in molecular biology is the prediction of functional sites in a genomic sequence, such as the “Translation Initiation Site”.

Contact Person(s)

For further information please contact:

Berberidis Christos

Academic Assistant, School of Science and Technology

Tel: +30 2310 807534
c.berberidis@ihu.edu.gr

Tjortjis Christos

Assistant Professor, School of Science and Technology

Selected Publications

  • Tzanis G., Berberidis C. and Vlahavas P. I., "StackTIS: A Stacked Generalization Approach for Effective Prediction of Translation Initiation Sites", Computers in Biology and Medicine, Elsevier, November 2011. (2011) • Journal Paper
  • Denaxas S. and Tjortjis C., "A GO-driven semantic similarity measure for quantifying the biological relatedness of gene products", Intelligent Decision Technologies journal, IOS Press, Vol. 3, No 4, pp. 239-248 (2009) • Journal Paper
  • Tzanis G., Berberidis C. and Vlahavas P. I., "Machine Learning and Data Mining in Bioinformatics", Handbook of Research on Innovations in Database Technologies and Applications: Current and Future Trends, Viviana E. Ferraggine, Jorge H. Doorn, and Laura C. Rivero (Eds.), IDEA Group Publishing, 978-1-60566-242-8, February 2009 (2009) • Book Chapter
  • Denaxas S. and Tjortjis C., "Scoring and summarizing gene product clusters using the Gene Ontology", Int’l Journal of Data Mining and Bioinformatics, Inderscience, Vol. 2, No. 3, pp.216- 235 (2008) • Journal Paper
  • Tzanis G., Berberidis C. and Vlahavas P. I., "MANTIS: A Data Mining Methodology for Effective Translation Initiation Site Prediction", Proc. of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Lyon, France, 2007 (2007) • Conference Paper

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