LogoMat-M
Profile Hidden Markov Models (pHMMs) are a widely used tool for protein family research.
We present a method to visualize all of their central aspects graphically, thus generalizing the concept of sequence logos introduced by Schneider and Stephens. For each emitting state of the pHMM, we display a stack of letters. As for sequence logos, the stack height is determined by the deviation of the position's letter emission frequencies from the background frequencies of the letters. As a new feature, the stack width now visualizes both the probability of reaching the state (the hitting probability) and the expected number of letters the state emits during a pass through the model (the expected contribution).
[Genome Research Limited]
Software
New to Logomat-M?
The About Logomat-M explains how to install and run the software and what most parts of the program do.
Server
- HMM Logo web server "LogoMat-M" - created and maintained by Benjamin Schuster-Böckler
Source code
- HMM-Logo source code - tar.gz archive of the Perl package
Publications
If you use HMM-Logos in your publication, please cite:
-
HMM Logos for visualization of protein families.
BMC bioinformatics 2004;5;7
PUBMED: 14736340; PMC: 341448; DOI: 10.1186/1471-2105-5-7
