The paper describes a new version of our software and resource with a number of new features implemented to make SMART more accessible to scientists from different fields. The new "Genomic" mode in SMART makes it easy to analyze domain architectures in completely sequenced genomes. The network context is now displayed in the results page for more than 350,000 proteins, enabling easy analyses of domain interactions.

Function prediction by homology is still a key to annotate genes and genomes, although the first widely used tools, such as fasta and blast, had been already developed in the 80s. (FASTA is an algorithm for rapid comparison and alignment of pairs of protein and DNA sequences developed for database searches. The BLAST algorithm was developed to perform similarity searches faster than FASTA.) SMART provides many manually derived profiles for protein domains, functional units of proteins that can be quickly scanned against large sequence data sets for their annotation. As it is sensitive and accurate, it is one of a few important tools used by a large community of genome researchers and molecular biologists.

I was one of a few researchers who identified many novel protein domains in the 80s and 90s. At that time, a new functional understanding using this domain knowledge was the research goal, but it became clear that, with the growing collection of domains, the identification of already classified domains in novel genes was equally important. Thus a number of domain databases had been established in the mid-90s, among them SMART. Over the years, more domains have been added and the tools have been improved.

We use SMART daily for many purposes in many very different projects such as genome annotation, domain network analysis, and the identification of binding sites for chemicals, to mention a few.

We do basic scientific research and thus, there are only interesting social aspects involving changes within the research field. For example, in the 90^th, the domain database developers were sort of competing. They have since learned, over time, to instead join forces and bundle their resources, which is much more beneficial for the scientific community.