__ellipsoidFN__: a tool for identifying a heterogeneous set of cancer biomarkers based on gene expressions
* Version 0.0.1
* Last updated: Nov. 1, 2012


!!!References

* Yong-Cui Wang, Nai-Yang Deng, and Yong Wang. Network predicting drug's anatomical therapeutic chemical code. ''Bioinformatics'', in revision.

!!!Motivation

Computationally identifying effective biomarkers for cancers from gene expression profiles is an important and challenging task. The challenge lies in the complicated pathogenesis of cancers that often involve the dysfunction of many genes and gene interactions. 

!!!Method

In this study, we proposed an efficient approach, called ellipsoidFN (ellipsoid Feature Net), that models the disease complexity by ellipsoids and seeks a set of heterogeneous biomarkers. The approach reduces the redundancy but improves the complementariness between the identified biomarkers, thus significantly enhancing the distinctiveness between cancers and normal samples and between cancer types. Evaluation on real prostate cancer, breast cancer and leukemia gene expression datasets suggested that our method outperforms the state-of-the-art biomarker identification methods, and it is a useful tool for cancer biomarker identification in the future. 

!!!Software

This version of the program is in very preliminary stage and provided just for testing purpose. The program is still under development.

* [ellipsoidFN.rar|ellipsoidFN.rar]