To obtain a comprehensive understanding of development, we need to characterize the anatomical, physiological, developmental, and molecular genetic properties of a wide range of different types of cells. However systematic organization of this information into databases and methods for rapid and easy access to such databases are still lacking; progress will be greatly promoted by solutions to this problem.
We propose to develop a relational database system and a widely accessible user interface to this database for genetic and developmental information from studies of the zebrafish. Zebrafish offer special advantages for this type of analysis at single cell resolution. The zebrafish, nearly unique among commonly studied vertebrates, contains large numbers of identifiable cells, some of which have already been characterized in terms of their detailed anatomical, physiological, developmental and genetic properties. Specifically, we propose:
To establish a database system for neuronal, genetic, and developmental zebrafish data. This will provide meaningful ways of relating various properties thus facilitating an understanding of their functions. To develop a WWW user interface to the database making it universally accessible for data submission and queries.
To integrate genetic and developmental information, we must share scientific results both within and between research communities. It will require the establishment of a collaborative group of labs to develop a common data model and the seamless integration of independent databases into a single logical data resource.
As a first step, help has already been solicited from a small number of labs that are willing to represent the zebrafish and mouse research communities to plan and implement this database system and we have tested initial designs for a user interface. The data for this system are already being generated by separately funded research projects.
The implementation of the database system will be coordinated with the mouse and human brain database projects. This will aid in understanding relationships among different vertebrates. Linking data describing synteny relationships, mutant phenotypes and gene expression patterns among species will provide tools for identifying new developmental genes and the molecular mechanisms of disease.
Our goal is to design this database system as a model which can also be used to organize information from other organisms.
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