Posts Tagged ‘Network Science’« Older Entries |
Monday, October 17, 2011
This group analyzes enzyme networks for robustness and dynamics.
Friday, October 14, 2011
The molecular, cellular, and evironemental factors of diabetes makes for a complex problem that this group attacks using a network analysis approach.
Tuesday, October 11, 2011
Lucy Shaprio and colleagues have identifed the minimal set of genes required for caulobacter to thrive on rich media. This work will help others bioengineer the organism to function in a variety of roles involving the production of small molecule metabolites and the generation of biosensor systems.
Friday, October 7, 2011
Cool tools for microbial bioinformatics from Berkeley Lab.
Thursday, October 6, 2011
Slime molds don’t sound very exciting but researchers are using them to optimize networks ranging from highway systems to disasters emergency response procedures. In this recent NYT Science Times piece, the research of several prominent labs is showcased.
In short, these organisms live as individual soil-dwelling cells and are content to survive on their basic food source: bacteria. But when food becomes scarce, these individuals send a chemical signal out to each other and a major change in physiology and strategy takes place. Some cells will sacrifice themselves for the great good of the group by filling themselves up with a carbohydrate that stiffens them (causing death). These cells serve as a scaffold support so that other cells can use this stalk as a structure to form spores, or cellular life rafts, that are capable of weathering the starvation conditions. Only when food becomes plentiful do the spores change back into individual cells to form a new colony.
The Bionetworks group in the Network Science Center is currently studying the modes of communication between cells as they respond not only to starvation conditions, but chemical contaminants of military interest as well.
Tuesday, September 20, 2011
Here’s an interesting take on the Krebs Cycle, and more importantly, learning the Krebs Cycle.
Monday, September 19, 2011
TimeDelay-ARACNE: Reverse engineering of gene networks from time-course data by an information theoretic approach.
Thursday, September 15, 2011
The timecourse data sets are huge in systems biology. This paper details efforts to generate gene networks using microarray data. Time-course data used to create a gene network
Wednesday, September 14, 2011
Tuesday, September 13, 2011
The construction of gene networks is tricky business and this group details a Rank-based edge method: Rank-based edge reconstruction