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Analysis and prediction of major blood proteins based on their amino acid and dipeptide composition

Muthukrishnan, S., Puri, M. and Lefevre, C. 2013, Analysis and prediction of major blood proteins based on their amino acid and dipeptide composition, International journal of bioinformatics research, vol. 5, no. 1, pp. 285-288, doi: 10.9735/0975-3087.5.1.285-288.

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Title Analysis and prediction of major blood proteins based on their amino acid and dipeptide composition
Author(s) Muthukrishnan, S.
Puri, M.ORCID iD for Puri, M. orcid.org/0000-0003-2469-3326
Lefevre, C.
Journal name International journal of bioinformatics research
Volume number 5
Issue number 1
Start page 285
End page 288
Total pages 4
Publisher Bioinfo Publications
Place of publication Mumbai, India
Publication date 2013
ISSN 0975-3087
0975-9115
Keyword(s) major blood proteins
amino acid composition
dipeptide composition
SVM
five-fold cross-validation technique
Summary A method has been developed for predicting blood proteins using the SVM based machine learning approach. In this prediction method a two-step strategy was deployed to predict blood proteins and their subclasses. We have developed models of blood proteins and achieved the maximum accuracies of 90.57% and 91.39% with Matthews correlation coefficient (MCC) of 0.89 and 0.90 using single amino acid and dipeptide composition respectively. Furthermore, the method is able to predict major subclasses of blood proteins; developed based on amino acid (AC) and dipeptide composition (DC) with a maximum accuracy 90.38%, 92.83%, 87.41%, 92.52% and 85.27%, 89.07%, 94.82%, 86.31 for albumin, globulin, fibrinogen, and regulatory proteins respectively. All modules were trained, tested, and evaluated using the five-fold cross-validation technique.
Language eng
DOI 10.9735/0975-3087.5.1.285-288
Field of Research 110106 Medical Biochemistry: Proteins and Peptides (incl Medical Proteomics)
Socio Economic Objective 970106 Expanding Knowledge in the Biological Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2013, Bioinfo Publications
Persistent URL http://hdl.handle.net/10536/DRO/DU:30082821

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