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Author (up) Ruz, G.A.; Goles, E. pdf  doi
  Title Learning gene regulatory networks using the bees algorithm Type
  Year 2013 Publication Neural Computing & Applications Abbreviated Journal Neural Comput. Appl.  
  Volume 22 Issue 1 Pages 63-70  
  Keywords Swarm intelligence; The bees algorithm; Simulated annealing; Boolean networks; Attractors  
  Abstract Learning gene regulatory networks under the threshold Boolean network model is presented. To accomplish this, the swarm intelligence technique called the bees algorithm is formulated to learn networks with predefined attractors. The resulting technique is compared with simulated annealing through simulations. The ability of the networks to preserve the attractors when the updating schemes is changed from parallel to sequential is analyzed as well. Results show that Boolean networks are not very robust when the updating scheme is changed. Robust networks were found only for limit cycle length equal to two and specific network topologies. Throughout the simulations, the bees algorithm outperformed simulated annealing, showing the effectiveness of this swarm intelligence technique for this particular application.  
  Address [Ruz, Gonzalo A.; Goles, Eric] Univ Adolfo Ibanez, Fac Ingn & Ciencias, Santiago 2640, Chile, Email:;  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0941-0643 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000313062100008 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 261  
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