Rawal, Prince: Combinatorics vs. Probability: DSGRN vs. RACIPE

Title: Combinatorics vs. Probability: DSGRN vs. RACIPE

Name: Prince Rawal

Major: Computer Science, Mathematics

School affiliation: School of Arts and Sciences

Programs: Aresty Summer Science Program

Other contributors: Marcio Gameiro, Konstantin Mischaikow, Aaron Scheiner

Abstract: We studied two different tools to study the dynamics of GeneRegulatory Networks. After gaining significant information on the background and how to use Random Circuit Perturbation (RACIPE) an application by Huang et al., we ran several test cases to recreate results obtained by the authors. Later, we moved on to Dynamic Signatures Generated by Regulatory Networks(DSGRN) developed by Cummins et al., which is relatively a recently developed application, and ran test cases on the same circuits, that were used in RACIPE. After understanding how to use similar testing conditions, we ran several test cases and compiled a table with integrated test results of both these applications. This table showed us the similarities between these applications, and for which parameters the data converges in these basic switches. Finally, we moved on to use this data to get DSGRN’s results in a more useful manner, which was done by weighing the parameter regions in DSGRN, according to the sampling in RACIPE.