Measuring the distance between multiple sequence alignments

By Benjamin P. Blackburne, Simon Whelan. 2012

77 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology

How researchers see this paper

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

In Genetics

1. Kazutaka Katoh
2. Daron M. Standley
3. Benjamin P. Blackburne
4. Simon Whelan
5. B. Faircloth
6. Steven Kelly
7. David M. Emms
8. Robert C. Edgar

In Molecular Biology

1. Daron M. Standley
2. Kazutaka Katoh
3. Benjamin P. Blackburne
4. Simon Whelan
5. B. Faircloth
6. Robert C. Edgar
7. Steven Kelly
8. David M. Emms

Citations in the corpus

• MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability (2013, background): “According to a recent comparative study based on the MetAl metric (Blackburne and Whelan 2012a, 2012b), there are two significantly different classes of MSA methods, similarity-based methods and evolution-based methods.”
• Class of multiple sequence alignment algorithm affects genomic analysis. (2013, methodology): “Using carefully selected sequence data from The Adaptive Evolution Database (TAED, Roth et al. 2005), we use recently developed distance metrics (Blackburne and Whelan 2012) to identify two significantly different classes of MSAM, discriminating between those that take an evolutionary approach to…”
• A simple method to control over-alignment in the MAFFT multiple sequence alignment program (2016, methodology): “According to Blackburne and Whelan (2012a), MSA methods can be classified into two types, similarity-based ones and evolution-based ones.”