title: Human polyomaviruses identification by logic mining techniques.
abstract: BACKGROUND
  Differences in genomic sequences are crucial for the classification of viruses into different species. In this work, viral DNA sequences belonging to the human polyomaviruses BKPyV, JCPyV, KIPyV, WUPyV, and MCPyV are analyzed using a logic data mining method in order to identify the nucleotides which are able to distinguish the five different human polyomaviruses.
  
  
  RESULTS
  The approach presented in this work is successful as it discovers several logic rules that effectively characterize the different five studied polyomaviruses. The individuated logic rules are able to separate precisely one viral type from the other and to assign an unknown DNA sequence to one of the five analyzed polyomaviruses.
  
  
  CONCLUSIONS
  The data mining analysis is performed by considering the complete sequences of the viruses and the sequences of the different gene regions separately, obtaining in both cases extremely high correct recognition rates.
authors.affiliation: Institute of Systems Analysis and Computer Science "A, Ruberti", National Research Council, Viale Manzoni 30, 00185 Rome, Italy. emanuel.weitschek@iasi.cnr.it
authors.forename: Emanuel
authors.initials: E
authors.lastname: Weitschek
authors.forename: Alessandra
authors.initials: A
authors.lastname: Lo Presti
authors.forename: Guido
authors.initials: G
authors.lastname: Drovandi
authors.forename: Giovanni
authors.initials: G
authors.lastname: Felici
authors.forename: Massimo
authors.initials: M
authors.lastname: Ciccozzi
authors.forename: Marco
authors.initials: M
authors.lastname: Ciotti
authors.forename: Paola
authors.initials: P
authors.lastname: Bertolazzi
mesh_terms: D001483:Base Sequence; D019295:Computational Biology / Q000379:methods*; D004279:DNA, Viral / Q000737:chemistry*; D057225:Data Mining; D006801:Humans; D011120:Polyomavirus / Q000145:classification* / Q000235:genetics*
chemical_list: D004279:DNA, Viral