The RAST server was brought up in 2007 and we published a description of the technology in 2008 The RAST Server: Rapid Annotations using Subsystems Technology.

The basic server was designed to support rapid annotation of prokaryotic genomes using subsystems technology.  We believe that the system is both unusually fast and unusually accurate.

RAST bases its attempts to achieve accuracy, consistency, and completeness on the use of a growing library of  subsystems that are manually curated and on protein families largely derived from the subsystems (FIGfams).

The RAST server automatically produces two classes of asserted gene functions: subsystem-based assertions are based on recognition of functional variants of subsystems, while nonsubsystem-based assertions are filled in using more common approaches based on integration of evidence from a number of tools. The fact that RAST distinguishes these two classes of annotation and uses the relatively reliable subsystem-based assertions as the basis for a detailed metabolic reconstruction makes the RAST annotations an exceptionally good starting point for a more comprehensive annotation effort.

Besides producing initial assignments of gene function and a metabolic reconstruction, the RAST server provides an environment for browsing the annotated genome and comparing it to the hundreds of genomes maintained within the SEED integration. The genome viewer included in RAST supports detailed comparison against existing genomes, determination of genes that the genome has in common with specific sets of genomes (or, genes that distinguish the genome from those in a set of existing genomes), the ability to display genomic context around specific genes, and the ability to download relevant information and annotations as desired.

To date, users have submitted over 14,000 jobs to the RAST server. We are planning enhancements to support processing phages, plasmids, and short fragments of DNA.  We are also developing a desktop version of  RAST, called myRAST, which will run on users' laptops (we will be targeting Macs and Windows machines initially).

You must have a RAST account to use RAST. The following videos show how to obtain an account.

Part 1: Registration

Part 2: Setting Your Password