Profile hidden Markov models (profile HMMs) are used as a popular bioinformatics tool for sensitive database searching, e.g. a set of not annotated protein sequences is compared to a database of profile HMMs to detect functional similarities. HMMer is a commonly used package for profile HMM-based methods. However, searching large databases with HMMer suffers from long runtimes on traditional computer architectures. These runtime requirements are likely to become even more severe due to the rapid growth in size of both sequence and model databases. In this paper, we present a new reconfigurable architecture to accelerate HMMer database searching. It is described how this leads to significant runtime savings on off-the-shelf field-programmable gate arrays (FPGAs).
Abstract The recent literature on profile hidden Markov model (profile HMM) methods and software is reviewed. Profile HMMs turn a multiple sequence alignment into a position-spe...
Abstract Summary: Although the HMMER package is widely used to produce profile hidden Markov models (profile HMMs) for protein domains, it has been difficult to create a profile...
Profile hidden Markov models (HMMs) are amongst the most successful procedures for detecting remote homology between proteins. There are two popular profile HMM programs, HMMER ...
HMMER is a software suite for protein sequence similarity searches using probabilistic methods. Previously, HMMER has mainly been available only as a computationally intensive U...
The HMMER webserver [http://www.ebi.ac.uk/Tools/hmmer] is a free-to-use service which provides fast searches against widely used sequence databases and profile hidden Markov mod...
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