@techreport{TR-IC-PFG-17-03,
   number = {IC-PFG-17-03},
   author  = {Flavio {Altinier} Maximiano da Silva and Andre Rodrigues
                   {Oliveira} and Zanoni {Dias}},
   title  =  {{Machine  Learning  Applied  to  Sorting Permutations by
                   Reversals and Transpositions}},
   month = {July},
   year = {2017},
   institution = {Institute of Computing, University of Campinas},
   note = {In English, 20 pages.
    \par\selectlanguage{english}\textbf{Abstract}
       The  problem  of determining relationship trees between genomes
       is  fundamental  when studying life evolution on the planet. As
       mutations  are  rare,  it  is  believed  that  when  one genome
       transforms into another, it probably used the fewest operations
       possible.  If  we represent genomes as numeric permutations, we
       reduce  that  problem  to the one of sorting permutations using
       specific operations. In this work we use two of the most common
       genome  mutations:  reversals  and transpositions. We propose a
       machine  learning  approach  where a classifier is trained on a
       set  of  features  of  small permutations and then used to sort
       bigger   permutations.   Results   show  that  this  method  is 
       competitive  when  compared  to others in literature, specially
       when dealing with small permutations or considering the others'
       maximum approximation factors.
  }
}