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Table 1.

Protein distribution in training dataset.

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Table 2.

Distribution of HSPs across different families in independent datasets.

HGNC dataset contains human HSPs obtained from HGNC [14] and mixed dataset contains rice HSPs obtained from Wang et al [15] and Sarkar et al [16].

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Fig 1.

Flow chart to show the prediction schema of HSPs and its families.

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Fig 2.

Schematic illustration of categorization of prediction into different categories.

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Fig 3.

Relative enrichment and depletion of amino acids in HSP and their families with reference to non-HSP and other HSP families respectively.

(3a) HSPs vs. Non-HSPs; (3b) HSP20 vs. remaining HSP family; (3c) HSP40 vs. remaining HSP family; (3d) HSP60 vs. remaining HSP family; (3e) HSP70 vs. remaining HSP family; (3f) HSP90 vs. remaining HSP family; (3g) HSP100 vs. remaining HSP family.

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Fig 3 Expand

Table 3.

Performance of discrete amino acid and coupled amino acid composition based SVM models during FFCV at 1st tier.

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Table 3 Expand

Table 4.

Performance of discrete amino acid and coupled amino acid composition based SVM models during LOOCV at 2nd tier.

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Fig 4.

ROC curve of SVM models based on amino acid and coupled amino acid composition for prediction of (4a) HSPs and (4b) different families of HSPs. Solid line represents discrete amino acid composition (AA) while broken represents coupled amino acid composition (CAA) based SVM model.

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Table 5.

Comparison of performance of PredHSP with iHSP-PseRAAAC at 2nd tier.

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Table 5 Expand

Table 6.

Performance of PredHSP on human HSPs obtained from HGNC [14] and rice HSPs obtained from Wang et al. [15] and Sarkar et al. [16].

TP represents true prediction and FP represents false prediction.

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Table 6 Expand

Table 7.

Genome wide annotation of heat shock proteins in different organisms.

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Table 7 Expand