Homology Detection via Family Pairwise Search

By William Noble Grundy. 1998

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Eric P. Nawrocki
2. Sean R. Eddy
3. Graham F. Hatfull
4. Diana L. Kolbe
5. Steven G. Cresawn
6. Matt Bogel
7. Ketil Malde
8. D. Jacobs-Sera

Citations in the corpus

• Accelerated Profile HMM Searches (2011, methodology): “For different programs, searches are performed either by constructing a single profile from the query alignment (HMMER3, HMMER2, SAM, PSI-BLAST), or by using “family pairwise search””
• Infernal 1.1: 100-fold faster RNA homology searches (2013, methodology): “We also tested two sequence-only methods: profile HMMs implemented in HMMER3 (Eddy, 2008, 2011) and family-pairwise (Grundy, 1998) single-sequence BLASTN queries (Altschul et al. , 1997), which were faster (0.02 and 0.01h, respectively), but significantly less sensitive than CMs, indicating the…”
• Phamerator: a bioinformatic tool for comparative bacteriophage genomics (2011, methodology): “We note that the use of efficient pairwise BLASTP comparisons to generate families of protein sequences has been described previously [31].”
• Query-Dependent Banding (QDB) for Faster RNA Similarity Searches (2007, methodology): “For comparison, BlastN was also benchmarked on these data using a family-pairwise search (FPS) procedure [39].”
• Infernal 1.0: inference of RNA alignments (2009, background): “[20], and also to family-pairwise-search with BLASTN [21, 22].”
• Increasing Sequence Search Sensitivity with Transitive Alignments (2013, methodology): “Combining or post-processing pairwise BLAST results is not a new approach, and e.g. taking the best alignment score between groups of sequences has been shown to identify protein family relationships with a higher sensitivity than using stochastic models, at least for small groups of sequences [15].”