As remarkably larger
and more complex data is available to both industry and
academia, systems that we struggle
for understanding become more
challenging. Latent structures and relationships are yet to be discovered.
Data need to be turned into information and knowledge.
Evidently, new algorithms are needed to be devised to cope with extraction of
inherently large and complex relationships that are usually represented
with graphs and networks.
Social networking is one simple example of a network that inhibits different relationship types and interactions between people. Another example would be protein interaction network that represents reciprocal work of proteins to perform a certain biological task. The situation or concept is based on graph and network algorithms from the theoretical aspect. Modeling and analysis of such networks require more scalable and robust algorithms.
We are a group of researchers@TOBB-ETU working on the analysis, modeling and visualization of structured data that covers XML documents, gene expression data, social interaction data, chemical compounds, and World Wide Web. All these different domains share one common feature that they have a set of complex relationships that can be represented as graphs (networks).
Self motivated and responsible students who are willing to work on these research-oriented topics are welcome. Please contact Mehmet Tan or Tansel Ozyer to join the group.
Social networking is one simple example of a network that inhibits different relationship types and interactions between people. Another example would be protein interaction network that represents reciprocal work of proteins to perform a certain biological task. The situation or concept is based on graph and network algorithms from the theoretical aspect. Modeling and analysis of such networks require more scalable and robust algorithms.
We are a group of researchers@TOBB-ETU working on the analysis, modeling and visualization of structured data that covers XML documents, gene expression data, social interaction data, chemical compounds, and World Wide Web. All these different domains share one common feature that they have a set of complex relationships that can be represented as graphs (networks).
Self motivated and responsible students who are willing to work on these research-oriented topics are welcome. Please contact Mehmet Tan or Tansel Ozyer to join the group.