- title = "An Evolutionary-based Approach for Feature Generation: Eukaryotic Promoter Recognition",
- author = "Uday Kamath and Kenneth {De Jong} and Amarda Shehu",
- pages = "277--284",
- booktitle = "Proceedings of the 2011 IEEE Congress on Evolutionary Computation",
- year = "2011",
- editor = "Alice E. Smith",
- month = "5-8 " # jun,
- address = "New Orleans, USA",
- organization = "IEEE Computational Intelligence Society",
- publisher = "IEEE Press",
- ISBN = "0-7803-8515-2",
- keywords = "genetic algorithms, genetic programming, SVM, eukaryotic DNA, eukaryotic promoter recognition, evolutionary-based approach, feature generation, genetic programming techniques, promoter region classification, promoter region identification, promoter region prediction, support vector machines, DNA, biology computing, genetics, pattern classification, support vector machines",
-
DOI = "
doi:10.1109/CEC.2011.5949629",
-
abstract = "Prediction of promoter regions continues to be a
challenging subproblem in mapping out eukaryotic DNA.
While this task is key to understanding the regulation
of differential transcription, the gene-specific
architecture of promoter sequences does not readily
lend itself to general strategies.
To date, the best approaches are based on Support Vector Machines (SVMs) that employ standard {"}spectrum{"} features and achieve promoter region classification accuracies from a low of 84percent to a high of 94percent depending on the particular species involved. In this paper, we propose a general and powerful methodology that uses Genetic Programming (GP) techniques to generate more complex and more gene-specific features to be used with a standard SVM for promoter region identification.
We evaluate our methodology on three data sets from different species and observe consistent classification accuracies in the 94-95percent range. In addition, because the GP-generated features are gene-specific, they can be used by biologists to advance their understanding of the architecture of eukaryotic promoter regions.",
- notes = "CEC2011 sponsored by the IEEE Computational Intelligence Society, and previously sponsored by the EPS and the IET.",
