A Software Architecture for Developmental Modeling in Plants: The Computable Plant Project

Victoria Gor, Bruce E. Shapiro, Henrik Jšnsson, Marcus Heisler, G. Venugopola Reddy, Elliot M. Meyerowitz and Eric Mjolsness

Presented at the Fourth International Conference on Bioinformatics of Genome Regulation and Structure (BGRS-2004), Novosibirsk, Russia, July 2004.

Abstract

Motivation. We present the software architecture of the Computable Plant Project, a multidisciplinary computationally based approach to the study of plant development. Arabidopsis thaliana is used as a model organism, and shoot apical meristem development as a model process. Meristems are the plant tissues where regulated cell division and differentiation lead to plant parts such as flowers and leaves. We are using green fluorescent proteins to mark specific cell types and acquire time series of threedimensional images via laser scanning confocal microscopy. To support this we have developed an interoperable architecture for experiment design that involves automated code generation, computational modeling, and image analysis.

Results. Automated image analysis, model fitting, and code generation allow us to explore alternative hypothesis in silico and guide in vivo experimental design. These predictions are tested using standard techniques such as mutants and altered hormone gradients. The present paper focuses on the automated code generation architecture.