Introduction

=Welcome to ZENBU=

ZENBU is a novel data integration system based around an enhanced "genome browser" interface concept. One of the key concepts in ZENBU is that of data-pooling. It is becoming much easier to do many experiments within a study. The simple process of managing different experimental combinations into different visualization tracks is becoming unmanagable. Data-pooling allows one to easily compare experimental expression within a series of related experiments that would previously require bioinformaticians to externally process each group analysis and upload each as a different data track. With ZENBU, the data can be loaded independently and the system can perform the pooling and group analysis. Because the system performs the pooling/group operations, the data can be interactively explored via region selection within a pooled track or through filtering of experiments within the pool. These realtime interactions within a pooled data track are immediately reflected in both the expression profile visualization and in the "experimental expression bar graph".

ZENBU also provides a platform for scientific data social-networking through a secured environment for data upload and controlled data sharing within user managed collaborations. Collaborations and data sharing are managed in a facebook style of "friend requests" providing users with the flexibility to create and manage their own collaborations without needing central adminstrators. ZENBU also provides guest access to view published, public data and without any data upload functions. User profiles are available to anyone and are managed through OpenID cooperation with major sites like google, yahoo, mixi and many others.

One of the key differences is that ZENBU allows for flexible data exploration through federated data integration and "on-demand" data processing within the system. This means that more raw or unprocessed data can be loaded into the ZENBU system, and then ZENBU can perform many of the basic data manipulations that previously required bioinformatics experts with knowledge of the unix command line and a collection of bioinformatics tools. This design also allows new data-sets to be added to the system integration while the system is running thus providing instant availablity of new data.