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MolEvolvR: A web-app for characterizing proteins using molecular evolution and phylogeny

View ORCID ProfileJoseph T Burke, Samuel Z Chen, Lo M Sosinski, John B Johnston, View ORCID ProfileJanani Ravi
doi: https://doi.org/10.1101/2022.02.18.461833
Joseph T Burke
1Department of Pathobiology and Diagnostic Investigation, Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824
2Genomics and Molecular Genetics Undergraduate Program, Michigan State University, East Lansing, MI 48824
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Samuel Z Chen
1Department of Pathobiology and Diagnostic Investigation, Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824
2Genomics and Molecular Genetics Undergraduate Program, Michigan State University, East Lansing, MI 48824
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Lo M Sosinski
1Department of Pathobiology and Diagnostic Investigation, Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824
3Computer Science Undergraduate Program, Michigan State University, East Lansing, MI 48824
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John B Johnston
5Center for Genomics-Enabled Plant Sciences, Michigan State University, East Lansing, MI 48824
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Janani Ravi
1Department of Pathobiology and Diagnostic Investigation, Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824
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  • For correspondence: janani@msu.edu
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Abstract

Studying proteins through the lens of evolution can help identify conserved features and lineage-specific variants, and potentially, their functions. MolEvolvR (http://jravilab.org/molevolvr) is a web-app that enables researchers to run a general-purpose computational workflow for characterizing the molecular evolution and phylogeny of their proteins of interest. The web-app accepts input in multiple formats: protein/domain sequences, homologous proteins, or domain scans. MolEvolvR returns detailed homolog data, along with dynamic graphical summaries, e.g., MSA, phylogenetic trees, domain architectures, domain proximity networks, phyletic spreads, and co-occurrence patterns across lineages. Thus, MolEvolvR provides a powerful, easy-to-use interface for computational protein characterization.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • http://jravilab.org/molevolvr/

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted February 22, 2022.
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MolEvolvR: A web-app for characterizing proteins using molecular evolution and phylogeny
Joseph T Burke, Samuel Z Chen, Lo M Sosinski, John B Johnston, Janani Ravi
bioRxiv 2022.02.18.461833; doi: https://doi.org/10.1101/2022.02.18.461833
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MolEvolvR: A web-app for characterizing proteins using molecular evolution and phylogeny
Joseph T Burke, Samuel Z Chen, Lo M Sosinski, John B Johnston, Janani Ravi
bioRxiv 2022.02.18.461833; doi: https://doi.org/10.1101/2022.02.18.461833

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