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AFSBN: A Method of Artificial Fish Swarm Optimizing Bayesian Network for Epistasis Detection

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Intro

  1. This is code of paper:

Liguang Wang#, Yujia Wang#, Yi Fu, Yunge Gao, Jiawei Du, Chen Yang, and Jianxiao Liu*. “AFSBN: A Method of Artificial Fish Swarm Optimizing Bayesian Network for Epistasis Detection”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 18, no. 4 (2019): 1369-1383.

  1. Paper link: https://ieeexplore.ieee.org/document/8884123/
  2. Special thanks to Yang Guo and bnlearn.

How to run

  1. hill-climbing.R is the most important file. All other files (except for argSet.R) are called here. It is based on hill-climbing designed in bnlearn pkg. So we keep the name.
  2. distance.R is for distance calculation.
  3. follow.R, prey.R, swarm.R are different behavior of fish.
  4. bulletin.R is for saving and comparing the fish with the max score.
  5. argSet.R is arguments we use.

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AFSBN: A Method of Artificial Fish Swarm Optimizing Bayesian Network for Epistasis Detection

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