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BMCBI
2004

HMM Logos for visualization of protein families

9 years 2 months ago
HMM Logos for visualization of protein families
Background: Profile Hidden Markov Models (pHMMs) are a widely used tool for protein family research. Up to now, however, there exists no method to visualize all of their central aspects graphically in an intuitively understandable way. Results: We present a visualization method that incorporates both emission and transition probabilities of the pHMM, thus extending sequence logos introduced by Schneider and Stephens. For each emitting state of the pHMM, we display a stack of letters. The stack height is determined by the deviation of the position's letter emission frequencies from the background frequencies. The stack width 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 state's expected contribution). A web interface offering online creation of HMM Logos and the corresponding source code can be found at the Logos web server of the Max Planck Institute for ...
Benjamin Schuster-Böckler, Jörg Schultz,
Added 16 Dec 2010
Updated 16 Dec 2010
Type Journal
Year 2004
Where BMCBI
Authors Benjamin Schuster-Böckler, Jörg Schultz, Sven Rahmann
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