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BacHbpred: support vector machine methods for the prediction of bacterial hemoglobin-like proteins

Selvaraj, MuthuKrishnan, Puri, Munish, Dikshit, Kanak L. and Lefevre, Christophe 2016, BacHbpred: support vector machine methods for the prediction of bacterial hemoglobin-like proteins, Advances in bioinformatics, vol. 2016, Article Number : 8150784, pp. 1-11, doi: 10.1155/2016/8150784.

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Title BacHbpred: support vector machine methods for the prediction of bacterial hemoglobin-like proteins
Author(s) Selvaraj, MuthuKrishnan
Puri, MunishORCID iD for Puri, Munish orcid.org/0000-0003-2469-3326
Dikshit, Kanak L.
Lefevre, Christophe
Journal name Advances in bioinformatics
Volume number 2016
Season Article Number : 8150784
Start page 1
End page 11
Total pages 11
Publisher Hindawi Publishing Corporation
Place of publication Cairo, Egypt
Publication date 2016
ISSN 1687-8027
Summary The recent upsurge in microbial genome data has revealed that hemoglobin-like (HbL) proteins may be widely distributed among bacteria and that some organisms may carry more than one HbL encoding gene. However, the discovery of HbL proteins has been limited to a small number of bacteria only. This study describes the prediction of HbL proteins and their domain classification using a machine learning approach. Support vector machine (SVM) models were developed for predicting HbL proteins based upon amino acid composition (AC), dipeptide composition (DC), hybrid method (AC + DC), and position specific scoring matrix (PSSM). In addition, we introduce for the first time a new prediction method based on max to min amino acid residue (MM) profiles. The average accuracy, standard deviation (SD), false positive rate (FPR), confusion matrix, and receiver operating characteristic (ROC) were analyzed. We also compared the performance of our proposed models in homology detection databases. The performance of the different approaches was estimated using fivefold cross-validation techniques. Prediction accuracy was further investigated through confusion matrix and ROC curve analysis. All experimental results indicate that the proposed BacHbpred can be a perspective predictor for determination of HbL related proteins. BacHbpred, a web tool, has been developed for HbL prediction.
Language eng
DOI 10.1155/2016/8150784
Field of Research 060102 Bioinformatics
Socio Economic Objective 970106 Expanding Knowledge in the Biological Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30082621

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Created: Fri, 08 Apr 2016, 10:29:54 EST

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.