EFICAz 2.5 – Accurate Sequence based Approach to Enzyme Function Inference

EFICAz 2.5


EFICAz2 (Enzyme Function Inference by a Combined Approach) is an automatic engine for large-scale enzyme function inference that combines predictions from six different methods developed and optimized to achieve high prediction accuracy: (i) recognition of functionally discriminating residues (FDRs) in enzyme families obtained by a Conservation-controlled HMM Iterative procedure for Enzyme Family classification (CHIEFc), (ii) pairwise sequence comparison using a family specific Sequence Identity Threshold, (iii) recognition of FDRs in Multiple Pfam enzyme families, (iv) recognition of multiple Prosite patterns of high specificity, (v) SVM evaluation of CHIEFc families, and (vi) SVM evaluation of Multiple Pfam enzyme families.



Center for the Study of Systems Biology






Arakaki A, Huang Y and Skolnick J (2009) EFICAz2: enzyme function inference by a combined approach enhanced by machine learningBMC Bioinformatics 10:107

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.