Interactive analysis of systems biology molecular expression data.
BACKGROUND
Systems biology aims to understand biological systems on a comprehensive scale, such that the components that make up the whole are connected to one another and work through dependent interactions. Molecular correlations and comparative studies of molecular expression are crucial to establishing interdependent connections in systems biology. The existing software packages provide limited data mining capability. The user must first generate visualization data with a preferred data mining algorithm and then upload the resulting data into the visualization package for graphic visualization of molecular relations.


RESULTS
Presented is a novel interactive visual data mining application, SysNet that provides an interactive environment for the analysis of high data volume molecular expression information of most any type from biological systems. It integrates interactive graphic visualization and statistical data mining into a single package. SysNet interactively presents intermolecular correlation information with circular and heatmap layouts. It is also applicable to comparative analysis of molecular expression data, such as time course data.


CONCLUSIONS
The SysNet program has been utilized to analyze elemental profile changes in response to an increasing concentration of iron (Fe) in growth media (an ionomics dataset). This study case demonstrates that the SysNet software is an effective platform for interactive analysis of molecular expression information in systems biology.
Zhang
Mingwu
M
Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA. mzhang2@purdue.edu
Ouyang
Qi
Q
Stephenson
Alan
A
Kane
Michael D
MD
Salt
David E
DE
Prabhakar
Sunil
S
Burgner
John
J
Buck
Charles
C
Zhang
Xiang
X
D000465:Algorithms; D003196:Computer Graphics; D003198:Computer Simulation; D003628:Database Management Systems; D016208:Databases, Factual; D020869:Gene Expression Profiling / Q000379:methods*; D016247:Information Storage and Retrieval; D008954:Models, Biological; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*; D012984:Software; D049490:Systems Biology / Q000379:methods; D018511:Systems Integration; D014584:User-Computer Interface
D020543:Proteome