A robust tool for discriminative analysis and feature selection in paired samples impacts the identification of the genes essential for reprogramming lung tissue to adenocarcinoma

@inproceedings{Toh2011ART,
  title={A robust tool for discriminative analysis and feature selection in paired samples impacts the identification of the genes essential for reprogramming lung tissue to adenocarcinoma},
  author={S. H. Toh and Philip Prathipati and Efthimios Motakis and Chee Keong Kwoh and Surya Pavan Yenamandra and Vladimir A. Kuznetsov},
  booktitle={BMC Genomics},
  year={2011}
}
BackgroundLung cancer is the leading cause of cancer deaths in the world. The most common type of lung cancer is lung adenocarcinoma (AC). The genetic mechanisms of the early stages and lung AC progression steps are poorly understood. There is currently no clinically applicable gene test for the early diagnosis and AC aggressiveness. Among the major reasons for the lack of reliable diagnostic biomarkers are the extraordinary heterogeneity of the cancer cells, complex and poorly understudied… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 12 CITATIONS

How to discriminate between potentially novel and considered biomarkers within molecular signature?

  • 2013 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
  • 2013
VIEW 4 EXCERPTS
CITES BACKGROUND

References

Publications referenced by this paper.
SHOWING 1-10 OF 70 REFERENCES

A direct approach to false discovery rates

VIEW 17 EXCERPTS
HIGHLY INFLUENTIAL

Data-driven Networking Reveals 5-Genes Signature for Early Detection of Lung Cancer

  • 2008 International Conference on BioMedical Engineering and Informatics
  • 2008
VIEW 10 EXCERPTS
HIGHLY INFLUENTIAL

Epidermal growth factor receptor mutations in plasma DNA samples predict tumor response in Chinese patients with stages IIIB to IV non-small-cell lung cancer.

  • Journal of clinical oncology : official journal of the American Society of Clinical Oncology
  • 2009
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL