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. 2012;8(1):34-9.
doi: 10.6026/97320630008034. Epub 2012 Jan 6.

A Classification Scoring Schema to Validate Protein Interactors

Free PMC article

A Classification Scoring Schema to Validate Protein Interactors

Prashanth Suravajhala et al. Bioinformation. .
Free PMC article

Abstract

Hypothetical protein [HP] annotation poses a great challenge especially when the protein is putatively linked or mapped to another protein. With protein interaction networks (PIN) prevailing, many visualizers still remain unsupported to the HP annotation. Through this work, we propose a six-point classification system to validate protein interactions based on diverse features. The HP data-set was used as a training data-set to find putative functional interaction partners to the remaining proteins that are waiting to be interacting. A Total Reliability Score (TRS) was calculated based on the six-point classification which was evaluated using machine learning algorithm on a single node. We found that multilayer perceptron of neural network yielded 81.08% of accuracy in modelling TRS whereas feature selection algorithms confirmed that all classification features are implementable. Furthermore statistical results using variance and co-variance analyses confirmed the usefulness of these classification metrics. It has been evaluated that of all the classification features, subcellular location (sorting signals) makes higher impact in predicting the function of HPs.

Keywords: hypothetical proteins; protein interaction networks; total reliability score.

Figures

Figure 1
Figure 1
A more reliable protein-protein interaction map for protein accession, NP_057673.2 based on the functional linkages.
Figure 2
Figure 2
Outcome of Anova on six-point classifiers using MATLAB. X-axis shows 1-6 classification schemes and TRS while Y-axis shows values corresponding to them.
Figure 3
Figure 3
Outcome of Kruskal_Wallis on six-point classifiers using MATLAB. X-axis shows 1-6 classification schemes and TRS while Y-axis shows values corresponding to them.

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