Deterministic Parallel Global Parameter Estimation for a Model of the Budding Yeast Cell Cycle

Two parallel deterministic direct search algorithms are combined to find improved parameters for a system of differential equations designed to simulate the cell cycle of budding yeast. Comparing the model simulation results to experimental data is difficult because most of the experimental data is qualitative rather than quantitative. An algorithm to convert simulation results to mutant phenotypes is presented. Vectors of the 143 parameters defining the differential equation model are rated by a discontinuous objective function. Parallel results on a 2200 processor supercomputer are presented for a global optimization algorithm, DIRECT, a local optimization algorithm, MADS, and a hybrid of the two. A second formulation is presented that uses a system of smooth inequalities to evaluate the phenotype of a mutant. Preliminary results of this formulation are given.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Computer Science

Department dc:contributor.department

Computer Science

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2006

Author dc:creator

• Panning, Thomas D.

Chair dc:contributor.committeechair

• Watson, Layne T.

Committee members dc:contributor.committeemember

• Tyson, John J.
• Shaffer, Clifford A.

• computational biology
• MADS algorithm
• direct search
• DIRECT algorithm

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

etd-05312006-175717

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/33360