ADI-Minebio: A Graph Mining Algorithm for Biomedical Data


  • Rodrigo de Sousa Gomide Goiano Federal Institute of Education, Science and Technology
  • Cristina Dutra de Aguiar Ciferri University of São Paulo
  • Ricardo Rodrigues Ciferri Federal University of São Carlos
  • Marina Teresa Pires Vieira Methodist University of Piracicaba



graph, graph mining, biomedical data, adjacency index


Graph mining is concerned with mining frequent subgraph patterns over a collection of graphs, aiming to find novel and useful knowledge. It has being used to analyze data from different domains, sometimes using algorithms tailored for a specific area of knowledge. In this paper, we propose a graph-mining algorithm and its application in the biomedical domain. We introduce the ADI-bio structure, which organizes data from a database with information of a disease’s patient, and also the ADI-Minebio algorithm, which performs a search on the proposed ADI-bio structure to find frequent subgraphs. Our approach is based on the ADI (adjacency index) structure and the ADI-Mine algorithm, but specifies a different structure and hence a new way of analyzing data through this structure. We also present a performance study to show the feasibility of our approach.


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How to Cite

Gomide, R. de S., Ciferri, C. D. de A., Ciferri, R. R., & Vieira, M. T. P. (2011). ADI-Minebio: A Graph Mining Algorithm for Biomedical Data. Journal of Information and Data Management, 2(3), 433.



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