Efficient selection of discriminative genes from microarray gene expression data for cancer diagnosis

@article{Huang2005EfficientSO,
  title={Efficient selection of discriminative genes from microarray gene expression data for cancer diagnosis},
  author={Di Huang and Tommy W. S. Chow and Eden W. M. Ma and Jinyan Li},
  journal={IEEE Transactions on Circuits and Systems I: Regular Papers},
  year={2005},
  volume={52},
  pages={1909-1918}
}
A new mutual information (MI)-based feature-selection method to solve the so-called large p and small n problem experienced in a microarray gene expression-based data is presented. First, a grid-based feature clustering algorithm is introduced to eliminate redundant features. A huge gene set is then greatly reduced in a very efficient way. As a result, the computational efficiency of the whole feature-selection process is substantially enhanced. Second, MI is directly estimated using quadratic… CONTINUE READING

Citations

Publications citing this paper.
Showing 1-10 of 11 extracted citations

Feature genes selection and classification with SVM for microarray data of lung tissue

2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS) • 2014
View 2 Excerpts

References

Publications referenced by this paper.
Showing 1-10 of 31 references

A comparative review of gene clustering in expression profile,

G. C. Tseng
Proc. 8th Int. Conf. on Control, Automation, Robotics and Vision (ICARCV), • 2004
View 1 Excerpt

Feature Extraction by Non-Parametric Mutual Information Maximization

Journal of Machine Learning Research • 2003
View 1 Excerpt

Input Feature Selection by Mutual Information Based on Parzen Window

IEEE Trans. Pattern Anal. Mach. Intell. • 2002
View 3 Excerpts

Similar Papers

Loading similar papers…