Welcome to EFICAz!

In the post-genomice era, computational methods for the inference of protein function are of great importance to both assist in as well as accelerate the functional annotation process. EFICAz (Enzyme Function Inference by Combined Approach) is an automatic engine for large-scale enzyme function inference that combines predictions from four different methods developed and optimized to achieve high prediction accuracy:

1. Recognition of functionally discriminating residues (FDRs) in enzyme families obtained by a Conservation-controlled HMM Iterative procedure for Enzyme Family classification (CHIEFc),
2. Pairwise sequence comparison using a family specific Sequence Identity Threshold,
3. Recognition of FDRs in Multiple Pfam enzyme families,
4. Recognition of multiple Prosite patterns of high specificity.

We have applied EFICAz for genome-wide enzyme function annotation on 245 genomes, including 21 archaea, 204 bacteria, and 20 eukaryotes. The average percentage of genes annotated with at least one EC number per genome is: 17.9%, 21.7%, and 13.1% for archaea, bacteria, and eukaryotes, respectively. To browse the annotation of individual genomes, please visit our Browse page. For comparison, enzyme annotation of these 245 genomes from current KEGG database can also be found in our Browse page.

EFICAz reference
To understand more details of EFICAz, please check out our NAR paper (Tian, W., Arakaki, A.K., Skolnick, J. (2004) EFICAz: a comprehensive approach for accur ate genome-scale enzyme function inference Nucleic Acids Res., 32, 6226-6239).