6533b86ffe1ef96bd12ce98a
RESEARCH PRODUCT
MAGA: A Supervised Method to Detect Motifs From Annotated Groups in Alignments
Pablo MierMiguel A. Andrade-navarrosubject
0303 health sciencesmultiple sequence alignmentsSequence analysisComputer science0206 medical engineeringMethods and ProtocolsSequence analysislcsh:Evolution02 engineering and technologyComputational biologyComputer Science Applications03 medical and health sciencesmotif findingcomputational biologyweb servicesGeneticslcsh:QH359-425020602 bioinformaticsEcology Evolution Behavior and Systematics030304 developmental biologydescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2020-04-01 | Evolutionary Bioinformatics |