explorase: Multivariate Exploratory Analysis and Visualization for Systems Biology

The datasets being produced by high-throughput biological experiments, such as microarrays, have forced biologists to turn to sophisticated statistical analysis and visualization tools in order to understand their data. We address the particular need for an open-source exploratory data analysis tool that applies numerical methods in coordination with interactive graphics to the analysis of experimental data. The software package, known as explorase, provides a graphical user interface (GUI) on top of the R platform for statistical computing and the GGobi software for multivariate interactive graphics. The GUI is designed for use by biologists, many of whom are unfamiliar with the R language. It displays metadata about experimental design and biological entities in tables that are sortable and filterable. There are menu shortcuts to the analysis methods implemented in R, including graphical interfaces to linear modeling tools. The GUI is linked to data plots in GGobi through a brush tool that simultaneously colors rows in the entity information table and points in the GGobi plots.

explorase: Multivariate Exploratory Analysis and Visualization for Systems Biology

The datasets being produced by high-throughput biological experiments, such as microarrays, have forced biologists to turn to sophisticated statistical analysis and visualization tools in order to understand their data. We address the particular need for an open-source exploratory data analysis tool that applies numerical methods in coordination with interactive graphics to the analysis of experimental data. The software package, known as explorase, provides a graphical user interface (GUI) on top of the R platform for statistical computing and the GGobi software for multivariate interactive graphics. The GUI is designed for use by biologists, many of whom are unfamiliar with the R language. It displays metadata about experimental design and biological entities in tables that are sortable and filterable. There are menu shortcuts to the analysis methods implemented in R, including graphical interfaces to linear modeling tools. The GUI is linked to data plots in GGobi through a brush tool that simultaneously colors rows in the entity information table and points in the GGobi plots

Acetyl-CoA in plant biology

Acetyl-CoA is found at the center of metabolism. This important metabolite is utilized within the cytosol of the plant for the biosynthesis of a large battery of important compounds via carboxylation, condensation or acetylation. The compounds that result from these three reactions include but are not limited to: flavonoids, sterols, elongated fatty acids utilized in cuticle and seed oil biosynthesis, mevalonate-derived isoprenoids, and specialized phytochemicals synthesized by polyketide synthases (PKS). The enzyme that synthesizes the cytosolic pool of acetyl-CoA is ATP-Citrate Lyase (ACL). When ACL activity is reduced in Arabidopsis thaliana, the resultant phenotype consists of a small, bonsai appearance, dark green leaves, hyper-accumulation of starch and anthocyanins and reduced accumulation of cuticular wax. Antisense-ACLA plants receiving malonate treatment do not hyper-accumulate starch or anthocyanins and they appear more wildtype (WT) in appearance. Transcriptomic and metabolomic data reveals large differences in antisense-ACLA plants and WT plants, but very few changes in antisense-ACLA plants treated with water as compared to those receiving malonate. Acetyl-CoA is utilized for the production of a number of specialized phytochemicals. Within the species Hypericum, a number of acetyl-CoA derived phytochemicals having bioactivity in mammalian systems have been identified including hypericin and hyperforin. Hypericum gentianoides was utilized as a medicinal plant by Native American Cherokees. Extracts from H. gentianoides have the ability to reduce the infectivity of HIV in HeLa37 cells and alter calcium hoeostatsis of HEK293 cells. The bioactive extracts contain several unusual acyl-phloroglucinols, saroaspidin A, uliginosin A and hyperbrasilol C. Saroaspidin A, uliginosin A and hyperbrasilol C accumulate in translucent glands found on the surface of H. gentianoides. The translucent glands found on H. gentianoides develop schizogenously, i.e., secretory cells within the gland pull away from each other in order to create an open cavity to store secretory product. As translucent glands age, changes in secretory cell wall integrity, plastid numbers, mitochondrial activity and cytoplasm density occur. Early in gland development, glands are surrounded by heavily osmium-stained material within peripherial cells and surrounding tissues, and presumably this staining becomes reduce over time as the chemical composition of both the surround tissues and glands changes. Acetyl-CoA is critical to the synthesis of important primary and specialized phytochemicals, and understanding the production and utilization of this metabolite is necessary.</p

explorase: Multivariate Exploratory Analysis and Visualization for Systems Biology

The datasets being produced by high-throughput biological experiments, such as microarrays, have forced biologists to turn to sophisticated statistical analysis and visualization tools in order to understand their data. We address the particular need for an open-source exploratory data analysis tool that applies numerical methods in coordination with interactive graphics to the analysis of experimental data. The software package, known as explorase, provides a graphical user interface (GUI) on top of the R platform for statistical computing and the GGobi software for multivariate interactive graphics. The GUI is designed for use by biologists, many of whom are unfamiliar with the R language. It displays metadata about experimental design and biological entities in tables that are sortable and filterable. There are menu shortcuts to the analysis methods implemented in R, including graphical interfaces to linear modeling tools. The GUI is linked to data plots in GGobi through a brush tool that simultaneously colors rows in the entity information table and points in the GGobi plots.This article is from Journal of Statistical Software 25 (2008): 1, doi: 10.18637/jss.v025.i09. Posted with permission.</p