Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers.

ABSTRACT:

Background

The development of new ortholog detection algorithms and the improvement of existing ones are of major importance in functional genomics. We have previously introduced a successful supervised pairwise ortholog classification approach implemented in a big data platform that considered several pairwise protein features and the low ortholog pair ratios found between two annotated proteomes (Galpert, D et al., BioMed Research International, 2015). The supervised models were built and tested using a Saccharomycete yeast benchmark dataset proposed by Salichos and Rokas (2011). Despite several pairwise protein features being combined in a supervised big data approach; they all, to some extent were alignment-based features and the proposed algorithms were evaluated on a unique t

SUBMITTER: Galpert D 

PROVIDER: S-EPMC5934817 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature