A Monte Carlo approach successfully identifies randomness in multiple sequence alignments: a more objective means of data exclusion.

By Bernhard Misof, Katharina Misof. Systematic Biology, 2009

354 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/e5f1e9ad40ee5afcc94f25f30466d65f9f8692bf

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. Alan R. Lemmon
2. E. Lemmon
3. H. Letsch
4. Patrick Kück
5. Roman R. Stocsits
6. Bernhard Misof
7. M. Borowiec

In Molecular Biology

1. Alan R. Lemmon
2. E. Lemmon
3. Patrick Kück
4. H. Letsch
5. Roman R. Stocsits
6. Bernhard Misof
7. M. Borowiec

In Plant Science

1. Alan R. Lemmon
2. E. Lemmon
3. Patrick Kück
4. H. Letsch
5. Roman R. Stocsits
6. Bernhard Misof

Citations in the corpus

• High-Throughput Genomic Data in Systematics and Phylogenetics (2013, background): “Both sources of error can result in random alignment of nonhomologous regions (Misof & Misof 2009) that introduce model misspecification at a fundamental level.”
• The impact of rRNA secondary structure consideration in alignment and tree reconstruction: simulated data and a case study on the phylogeny of hexapods. (2010, methodology): “The following settings of Aliscore were used: Window size was set to four positions, gaps were treated as ambiguous characters, and the maximum number of possible pairwise comparisons were applied.”