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# Table 1 Overall framework of the HEPT method

 Algorithm 1: HEPT method Input: A PPI network G, protein domain, GO annotation, orthologs datasets, subcellular localization datasets; stopping threshold ε Output: Top N proteins sorted by VA in descending order Step 1. Construct the tensor T according to Equation (1), (2), (3), (4)Step 2. Calculate jump probability vector D with Equation (12), (13), (14), (15) Step 3. Construct two transition probability tensors T(a) , T(h), and T(e) with Equation (6)-(8) Step 4. Initialize VA0 = 1/n, VH0 = 1/n, VE0 = 1/m Step 5. Let t = 1 Step 6. Calculate VAt = (1 − α) × D + α × T(a) × VHt − 1VEt − 1 Step 7. Calculate VHt = T(h) × VAt × VEt − 1Step 8. Calculate VEt = T(e) × VAt × VHt Step 9. If ‖VAt − VAt − 1‖ + ‖VHt − VHt − 1‖ + ‖VEt − VEt − 1‖ ≥ ε, then let VA = VAt, VH = VHt, VE = VEt. Otherwise, let t = t + 1, and then go to Step 6. Step 10. Sort proteins by the value of VA in the descending order Step 11. Output top N of sorted proteins 