Kinomer Method
Profile Hidden Markov Models
Profile hidden Markov models (HMMs) are statistical descriptions of sequence conservation from multiple sequence alignments, and have been shown to outperform standard pairwise sequence comparison methods, both in terms of sensitivity and specificity. HMMs form the basis of protein family and domain description libraries such as SUPERFAMILY and Pfam. Kinomer v.1.0 is a multi-level library of HMMs where each protein kinase group is represented by a number of HMMs, thereby achieving great sensitivity and specificity for searching and classifying protein kinases automatically into groups.
Running Kinomer locally
Sequences can be searched against the Kinomer library using the hmmpfam program from the HMM software suite HMMer. This is freely available for download from HMMer can be readily installed on a variety of Linux and UNIX platforms (including Mac OS/X). The user manual , which is also available from the HMMer web site, will guide you through the process of running your HMM searches locally.
The Kinomer v.1.0 HMM library is available for download from this site.