Sentence examples for using the hmmer toolkit from inspiring English sources

Next, a hidden Markov model (HMM) was generated from these aligned sequences using the HMMer Toolkit (25), and the HMM was subsequently used to search RefSeq (26) to identify additional members of the homeodomain family.

The sequence logos of bZIP domains were created using the HMMER online tool (hmmer.janelia.org/search/hmmsearch) [ 30].

Domains within the sequences were identified by searching against the Pfam database [69] using the HMMER v3 program [70].

All HMMs were constructed using the HMMER package hmmbuild and hmmcalibrate commands, and sequences aligned to the HMMs were extracted from the output of the hmmpfam command (package available at http://hmmer.janelia.org).org

Conserved protein domains were identified using the HMMer package [ 83].

The HMMs were trained on this alignment using the HMMer programme's (Eddy, 1998) HMMBuild.

HET domain [ 15, 33] proteins were identified using the HMMer package as described in Methods.

From the alignments, sequence Hidden Markov Models (HMMs) were constructed using the HMMER 2.2 package [ 30].

Alternatively, profile-based search methods using the HMMER algorithm may also be used whenever pre-computed sequence profiles are available.

Searches using profile Hidden Markov Models (HMMs) from the PFAM database [ 43] were done using the HMMer software package.

The C. briggsae and C. remanei TFs were identified using the HMMER [ 22, 65] and InParanoid programs [ 21].