Alignment-free genome comparison with feature frequency profiles (FFP) and optimal resolutions
By Gregory E. Sims, Se-Ran Jun, G. Wu, Sung-Hou Kim. Proceedings of the National Academy of Sciences of the United States of America, 2009
427 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/921a6174fe50e2788ea1aa249048c94841be4968
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In Artificial Intelligence
In Molecular Biology
- Andrzej Zielezinski
- W. Karłowski
- Jonas S. Almeida
- Susana Vinga
- Heath E. O’Brien
- J. Díaz-Valderrama
- M. Catherine Aime
- Bryn T. M. Dentinger
Citations in the corpus
- Alignment-free sequence comparison: benefits, applications, and tools (2017, background): “As a rule of thumb, smaller k -mers should be used when sequences are obviously different (e.g., they are not related) whereas longer k -mers can be used for very similar sequences [55, 58].”
- Tales from the crypt: genome mining from fungarium specimens improves resolution of the mushroom tree of life (2016, methodology): “Alternative approaches to analysing protein-coding genome data (e.g. nucleotide-based analyses) or using alignmentfree genome similarity methods (Sims et al., 2008), or approaches that target different types of data (e.g. genome skimming, targeted enrichment, ultraconserved elements: Faircloth et…”