PASTA: Ultra-Large Multiple Sequence Alignment for Nucleotide and Amino-Acid Sequences

By Siavash Mirarab, Nam-phuong Nguyen, Sheng Guo, Li-San Wang, Junhyong Kim, Tandy J. Warnow. J. Comput. Biol., 2015

378 citations recorded by the source corpus.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/bb355af0129f55881af7bc3edf3188db0b786e64

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In Molecular Biology

1. Connor R. Fitzpatrick
2. Matthew R. McKay
3. Pauline W. Wang
4. David S. Guttman
5. Marc T. J. Johnson
6. J. Copeland
7. P. Kotanen
8. Syed Faraz Ahmed

Citations in the corpus

• Assembly and ecological function of the root microbiome across angiosperm plant species (2018, methodology): “We used PASTA to align ASV sequences and build a maximum-likelihood phylogenetic tree (64).”
• DECIPHER: harnessing local sequence context to improve protein multiple sequence alignment (2015, neutral): “I next compared DECIPHER to PASTA [14], which is a program intended to extend the accuracy of less-scalable algorithms to large alignments.”
• Preliminary Identification of Potential Vaccine Targets for the COVID-19 Coronavirus (SARS-CoV-2) Based on SARS-CoV Immunological Studies (2020, methodology): “4 (Mirarab et al., 2015) to construct a maximum-likelihood phylogenetic tree of each structural protein using the available sequence data of SARS-CoV, MERS-CoV, and 2019-nCoV.”