Open AccessImproved enzyme annotation with EC-specific cutoffs using DETECT v2
Author(s) -
Nirvaursimulu,
Leon L. Xu,
James D. Wasmuth,
Ivan Krukov,
John Parkinson
Publication year - 2018
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bty368
Subject(s) - annotation , computer science , enzyme , artificial intelligence , chemistry , biochemistry
We present DETECT v2-an enzyme annotation tool which considers the effect of sequence diversity when assigning enzymatic function [as an Enzyme Commission (EC) number] to a protein sequence. In addition to capturing more enzyme classes than the previous version, we now provide EC-specific cutoffs that greatly increase precision and recall of assignments and show its performance in the context of pathways.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom