Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Motivation: Given the vast amount of gene expression data, it is essential to develop a simple and reliable method of investigating the fine structure of gene interaction.  show how an information geometric measure achieves this. Results:  introduce an information geometric measure of binary random vectors and show how this measure reveals the fine structure of gene interaction. In particular,  propose an iterative procedure by using this measure (called IPIG). The procedure finds higher-order dependencies which may underlie the interaction beten two genes of interest. To demonstrate the method,  investigate the interaction beten the two genes of interest in the data from human acute lymphoblastic leukemia cells. The method successfully discovered biologically known findings and also selected other genes as hidden causes that constitute the interaction. Availability: Softwares are currently not available but are possibly made available in future at http://www.mns. brain.riken.go.jp/∼nakahara/DNA pub.html, where all the related information is also linked.
['Hiroyuki Nakahara', 'Shin Ichi Nishimura', 'Masato Inoue', 'Gen Hori', 'S. Amari']
I am writing a research paper on a idea Gene interaction in DNA microarray data is decomposed by information geometric measure
[{"from": "human", "value": "I am writing a research paper on a idea Gene interaction in DNA microarray data is decomposed by information geometric measure"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Motivation: Given the vast amount of gene expression data, it is essential to develop a simple and reliable method of investigating the fine structure of gene interaction.  show how an information geometric measure achieves this. Results:  introduce an information geometric measure of binary random vectors and show how this measure reveals the fine structure of gene interaction. In particular,  propose an iterative procedure by using this measure (called IPIG). The procedure finds higher-order dependencies which may underlie the interaction beten two genes of interest. To demonstrate the method,  investigate the interaction beten the two genes of interest in the data from human acute lymphoblastic leukemia cells. The method successfully discovered biologically known findings and also selected other genes as hidden causes that constitute the interaction. Availability: Softwares are currently not available but are possibly made available in future at http://www.mns. brain.riken.go.jp/\u223cnakahara/DNA pub.html, where all the related information is also linked."}]