A new generation of homology search tools based on probabilistic inference.
By Sean R. Eddy. 2009
1,358 citations recorded by the source corpus.
Subfields: Molecular Biology
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In Molecular Biology
- Yang Zhang
- Johannes Söding
- Jinbo Xu
- David Baker
- Sergey Ovchinnikov
- David T. Jones
- Burkhard Rost
- Sheng Wang
Citations in the corpus
- HH-suite3 for fast remote homology detection and deep protein annotation (2019, methodology): “Therefore, to find template proteins for comparative protein structure modeling and for deep functional annotation, the most sensitive search tools such as HMMER [3, 4] and HHblits [5] are often used [6–9].”
- Robust and accurate prediction of residue–residue interactions across protein interfaces using evolutionary information (2014, methodology): “1b package [ Eddy, 2009 ]).”
- Large-scale determination of previously unsolved protein structures using evolutionary information (2015, methodology): “N 8, [ Eddy, 2009 ]) with uniref100 database ( Suzek et al., 2007 ) from January, 2015 and eliminated identical sequences and sequences aligned over less than 75% of the protein; the number of remaining sequences for each of the 58 families is listed in Table 2 .”
- Ranking non-synonymous single nucleotide polymorphisms based on disease concepts (2014, methodology): “In brief, an ab initio hidden Markov model (HMM), representing the multiple sequence alignment of homologous (both orthologous and/or paralogous) sequences within the Swis-sProt/TrEMBL [16] database, is constructed using the HMMER3 [17] software suite.”
- Phytozome: a comparative platform for green plant genomics (2011, methodology): “Multiple sequence alignments of each family’s founding members are created using MUSCLE, and the alignments are used by HMMER3 to create hidden Markov model profiles.”
- Systematic identification of long noncoding RNAs expressed during zebrafish embryogenesis. (2012, methodology): “Second, the putatively noncoding transcripts and the ‘‘gray’’ set transcripts were repeat-masked and subjected to blastx, blastp, and HMMER (versus Pfam-A and Pfam-B) (Eddy 2009).”
- Evaluation of methods for modeling transcription-factor sequence specificity (2013, methodology): “We identified the DNA Binding Domain (DBD) of each TF by searching for Pfam domains 51 using the HMMER tool 52 .”