@article{799710,
      recid = {799710},
      author = {Fassetti, Fabio, and Rombo, Simona E., and Serrao,  Cristina,},
      title = {Discriminative pattern discovery on biological networks /},
      pages = {1 online resource.},
      abstract = {This work provides a review of biological networks as a  model for analysis, presenting and discussing a number of  illuminating analyses. Biological networks are an effective  model for providing insights about biological mechanisms.  Networks with different characteristics are employed for  representing different scenarios. This powerful model  allows analysts to perform many kinds of analyses which can  be mined to provide interesting information about  underlying biological behaviors. The text also covers  techniques for discovering exceptional patterns, such as a  pattern accounting for local similarities and also  collaborative effects involving interactions between  multiple actors (for example genes). Among these  exceptional patterns, of particular interest are  discriminative patterns, namely those which are able to  discriminate between two input populations (for example  healthy/unhealthy samples). In addition, the work includes  a discussion on the most recent proposal on discovering  discriminative patterns, in which there is a labeled  network for each sample, resulting in a database of  networks representing a sample set. This enables the  analyst to achieve a much finer analysis than with  traditional techniques, which are only able to consider an  aggregated network of each population.},
      url = {http://library.usi.edu/record/799710},
}