Naren Ramakrishnan and Richard F. Helm Departments of Computer Science and Biochemistry Virginia Tech, Blacksburg, VA 24061

 What we do  How we do it  Some discussion of biological results

From multivariate time course data, reconstruct (i) stages, (ii) transitions between stages, and (iii) properties that hold in each stage

Kripke structures

 Yeast store carbohydrate and burn it in late G1 phase of the cell cycle: this superimposes a metabolic cycle over the cell cycle  Sequence of oxidative and reductive phases ◦ O2 is used up to burn carbohydrates during oxidative phase ◦ O2 levels increase and carbohydrate is stored in the reductive phase  Interplay between the YCC and YMC lead to compartmentalization of biological processes in time ◦ Cell cycle : reductive phase ◦ Glycolysis and respiration occur at different times

 Segment the time course  Identify biological processes enriched in each segment  Convert segmentation to a Kripke structure  Merge Kripke structures into a dynamic temporal model

 How do we identify “breakpoints” in the time course?  Intuition: A breakpoint is where there is significant reorganization of clusters around segment boundaries.

3602 genes, 3 clusters

Algorithm optimizes for this!

Gantt chart of MD treatment