Construction of Gene Regulatory Networks Using Recurrent Neural Networks and Swarm Intelligence

<table class="table-group" id="tab7"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left">Technique</td><td class="align_center">BAPSO_full</td><td class="align_center">BAPSO_half</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left">Correct interactions</td><td class="align_center">metJ → metN, metJ → folE, and metR → metL</td><td class="align_center">metJ → metN, metJ → metC, metJ → metQ, phoP → yrbL, and phoP → borD</td></tr><tr><td class="align_left">Computational time</td><td class="align_center">3.2 hrs</td><td class="align_center">1.7 hrs</td></tr><tr><td class="align_left">MSE</td><td class="align_center">0.0031</td><td class="align_center">0.0034</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

True positives obtained for the GRN consisting of 20 genes.

Scientifica

tab7

Table 7

Table 7: Construction of Gene Regulatory Networks Using Recurrent Neural Networks and Swarm Intelligence 