Harnessing the evolutionary information on oxygen binding proteins through Support Vector Machines based modules.

ABSTRACT:

Objectives

The arrival of free oxygen on the globe, aerobic life is becoming possible. However, it has become very clear that the oxygen binding proteins are widespread in the biosphere and are found in all groups of organisms, including prokaryotes, eukaryotes as well as in fungi, plants, and animals. The exponential growth and availability of fresh annotated protein sequences in the databases motivated us to develop an improved version of "Oxypred" for identifying oxygen-binding proteins.

Results

In this study, we have proposed a method for identifying oxy-proteins with two different sequence similarity cutoffs 50 and 90%. A different amino acid composition based Support Vector Machines models was developed, including the evolutionary profiles in the form position-specific

SUBMITTER: Muthukrishnan S 

PROVIDER: S-EPMC5948687 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature