2010

Conférence

Pattern Recognition in Bioinformatics. PRIB 2010. Lecture Notes in Computer Science, vol 6282, pp 219–229

In the context of microarray data analysis, biclustering aims to identify simultaneously a group of genes that are highly correlated across a group of experimental conditions. This paper presents a Biclustering Iterative Local Search (BILS) algorithm to the problem of biclustering of microarray data. The proposed algorithm is highlighted by the use of some original features including a new evaluation function, a dedicated neighborhood relation and a tailored perturbation strategy. The BILS algorithm is assessed on the well-known yeast cell-cycle dataset and compared with two most popular algorithms.

@inproceedings{AyadiEH10,
  author       = {Wassim Ayadi and
                  Mourad Elloumi and
                  Jin{-}Kao Hao},
  editor       = {Tjeerd Dijkstra and
                  Evgeni Tsivtsivadze and
                  Elena Marchiori and
                  Tom Heskes},
  title        = {Iterated Local Search for Biclustering of Microarray Data},
  booktitle    = {Pattern Recognition in Bioinformatics - 5th {IAPR} International Conference,
                  {PRIB} 2010, Nijmegen, The Netherlands, September 22-24, 2010. Proceedings},
  series       = {Lecture Notes in Computer Science},
  volume       = {6282},
  pages        = {219--229},
  publisher    = {Springer},
  year         = {2010},
  url          = {https://doi.org/10.1007/978-3-642-16001-1\_19},
  doi          = {10.1007/978-3-642-16001-1\_19}
}