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

Muthukrishnan, Selvaraj and Puri, Munish 2018, Harnessing the evolutionary information on oxygen binding proteins through Support Vector Machines based modules, BMC research notes, vol. 11, pp. 1-8, doi: 10.1186/s13104-018-3383-9.

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Title Harnessing the evolutionary information on oxygen binding proteins through Support Vector Machines based modules
Author(s) Muthukrishnan, Selvaraj
Puri, MunishORCID iD for Puri, Munish orcid.org/0000-0003-2469-3326
Journal name BMC research notes
Volume number 11
Article ID 290
Start page 1
End page 8
Total pages 8
Publisher BMC
Place of publication London, Eng.
Publication date 2018
ISSN 1756-0500
Keyword(s) Oxygen binding proteins
Hemoglobin
Myoglobin
Leghemoglobin
Erythrocruorin
Hemerythrin
Hemocyanin
Support Vector Machines
Confusion matrix
ROC Analysis
Summary 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 scoring matrix (PSSM). The fivefold cross-validation techniques were applied to evaluate the prediction performance. Also, we compared with existing methods, which shows nearly 97% recognition, but, our newly developed models were able to recognize almost 99.99 and 100% in both oxy-50 and 90% similarity models respectively. Our result shows that our approaches are faster and achieve a better prediction performance over the existing methods. The web-server Oxypred2 was developed for an alternative method for identifying oxy-proteins with more additional modules including PSSM, available at http://bioinfo.imtech.res.in/servers/muthu/oxypred2/home.html.
Language eng
DOI 10.1186/s13104-018-3383-9
Field of Research 1199 Other Medical And Health Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2018 The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30113373

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.