
Finding the balance between the mathematical and biological optima in multiple sequence alignment
Author(s) -
Maria Anisimova,
Gina Cannarozzi,
David A. Liberles
Publication year - 2010
Publication title -
trends in evolutionary biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.259
H-Index - 8
eISSN - 2036-265X
pISSN - 2036-2641
DOI - 10.4081/eb.2010.e7
Subject(s) - variety (cybernetics) , computer science , sequence (biology) , data science , artificial intelligence , management science , machine learning , biology , engineering , genetics
Recent advances in evolutionary modelling and alignment methodology mean that today accurate and fast algorithms exist for aligning sequences with special features and incorporating structural and functional information. However, our reviewing experience and a recent study by Morrison (1) suggest that older and thus worse performing methods are predominantly used (especially in the communities of molecular systematics and experimental biology), and the resulting alignments are then curated manually. Most often, no clear biological reasoning is invoked during manual alignment, but rather its aesthetic qualities, as measured by eye are used. Such subjectivity is not consistent with core scientific principles. Although we recognize that methodological problems still exist, computerized alignment methods are currently more realistic and may account for a variety of factors. Here we argue that modern methodology is not utilized to its full potential, and thus discuss the advantages of certain recent methods so to encourage their greater use. We also suggest future directions for the further improvement of automatic alignment methods based upon disconnects of existing methods with underlying biological mechanisms