| HMM
Performance
Hidden Markov Model and Profilesearch
analyses can provide unique benefits over sequence-based analyses.
Because they provide more probabilisitcally correct modeling, these
searches be more accurate for evolutionarily distant
relationships. The PFAM, TIGRfam and Superfamily HMM databases
are excellent tools for idenifying the family to which a protein
or
domain belongs. Searching these databases is dramatically
faster on DeCypher than on CPU and cluster-based solutions.

1000 GOS Proteins compared
to PFAM 22.0
A CodeQuest biocomputing workstation reduced the
runtime of a large HMMpfam Search from
23.67 hours down to 2.5 minutes, for a performance equivalent to 568 CPU cores. This search was performed on a CodeQuest X9 with 2 DeCypher Engines, compared to running HMMer software on a single core 2.33 GHz CPU.
Establishing novel protein families is critical for metagenomics studies. Currently, several institutions employ TimeLogic solutions for their metagenomics projects, including The Scripps Genome Center, DoE Joint Genome Institute, The Salk Institute Max Planck and Argonne National Labs.


Interested in further discussion
of our benchmark data? Would you like to see custom benchmarks for
your toughest bioinformatics bottlenecks? Contact
a TimeLogic account executive today to learn more about CodeQues or DeCypher!
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