From: A novel method to predict essential proteins based on tensor and HITS algorithm

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 VA_{0} = 1/n, VH_{0} = 1/n, VE_{0} = 1/m | |

Step 5. Let t = 1 | |

Step 6. Calculate VA_{t} = (1 − α) × D + α × T^{(a)} × VH_{t − 1}VE_{t − 1} | |

Step 7. Calculate VH_{t} = T^{(h)} × VA_{t} × VE_{t − 1}Step 8. Calculate VE _{t} = T^{(e)} × VA_{t} × VH_{t} | |

Step 9. If ‖VA_{t} − VA_{t − 1}‖ + ‖VH_{t} − VH_{t − 1}‖ + ‖VE_{t} − VE_{t − 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 |