ArticleEvolutionary bioinformatics online2020
MAGA: A Supervised Method to Detect Motifs From Annotated Groups in Alignments.
Article in Evolutionary bioinformatics online, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Phylogenetic and transcriptomic characterization of insulin and growth factor receptor tyrosine kinases in crustaceans.Frontiers in endocrinology · 2024Article
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2 authors.
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Abstract
Multiple sequence alignments are usually phylogenetically driven. They are studied in the framework of evolution. But sometimes, it is interesting to study residue conservation at positions unconstrained by evolutionary rules. We present a supervised method to access a layer of information difficult to appreciate visually when many protein sequences are aligned. This new tool (MAGA; http://cbdm-01.zdv.uni-mainz.de/~munoz/maga/) locates positions in multiple sequence alignments differentially conserved in manually defined groups of sequences.
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Registered trials
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