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MAGA: A Supervised Method to Detect Motifs From Annotated Groups in Alignments.

Pablo MierMiguel A Andrade-Navarro
Published in: Evolutionary bioinformatics online (2020)
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.
Keyphrases
  • machine learning
  • amino acid
  • transcription factor
  • genome wide
  • health information
  • dna methylation
  • genetic diversity