Identification of functionally important and evolutionarily significant sequence profiles

              It has been long known that evolutionarily related sequences can be identified by multiple sequence alignments (MSA). Also it has been seen that protein structure prediction can be easily done using multiple alignments of sequences. The various possible multiple alignments of protein sequences are analyzed to work out the most appropriate alignment .

              Recently Gil N. et al.(2018) have presented a new method to select the one best MSA out of the plethora of alignments. They have already done the analysis for 435 protein sequences. The information has been collected for both protein- protein interaction and protein ligand interaction.

             The software is freely available at the following URL: https://github.com/nelsongil92/SAMMI.git

Reference:

Gil N. et al.(2018) Identifying functionally informative evolutionary sequence profiles. Bioinformatics 34(8): 1278-1286

 

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