title: Data-intensive analysis of HIV mutations.
abstract: In this study, clustering was performed using a bitmap representation of HIV reverse transcriptase and protease sequences, to produce an unsupervised classification of HIV sequences. The classification will aid our understanding of the interactions between mutations and drug resistance. 10,229 HIV genomic sequences from the protease and reverse transcriptase regions of the pol gene and antiretroviral resistant related mutations represented in an 82-dimensional binary vector space were analyzed.
  
  
  
  A new cluster representation was proposed using an image inspired by microarray data, such that the rows in the image represented the protein sequences from the genotype data and the columns represented presence or absence of mutations in each protein position.The visualization of the clusters showed that some mutations frequently occur together and are probably related to an epistatic phenomenon.
  
  
  
  We described a methodology based on the application of a pattern recognition algorithm using binary data to suggest clusters of mutations that can easily be discriminated by cluster viewing schemes.
authors: Department of Computer Science - DCC, University of São Paulo, Rua do Matão, 1010, CEP 05508-090 São Paulo, SP, Brazil. mina.cintho@usp.br.
authors: Mina Cintho
authors: MC
authors: Ozahata
authors: Sangue Foundation, Health State Secretary, Department of Molecular Biology, Serology Division, Av Dr Enéas de Carvalho Aguiar, Cerqueira Cesar, CEP 05403-000 São Paulo, 155, SP, Brazil. sabinoec@gmail.com.
authors: Ester Cerdeira
authors: EC
authors: Sabino
authors: Federal University of São Paulo, Rua Pedro de Toledo, São Paulo, 669, CEP 04039-032, SP, Brazil. rsdiaz@catg.com.br.
authors: Ricardo Sobhie
authors: RS
authors: Diaz
authors: Department of Computer Science - DCC, University of São Paulo, Rua do Matão, 1010, CEP 05508-090 São Paulo, SP, Brazil. cesar@ime.usp.br.
authors: Roberto M
authors: RM
authors: Cesar
authors: Sangue Foundation, Health State Secretary, Department of Molecular Biology, Serology Division, Av Dr Enéas de Carvalho Aguiar, Cerqueira Cesar, CEP 05403-000 São Paulo, 155, SP, Brazil. jef@ime.usp.br.
authors: João Eduardo
authors: JE
authors: Ferreira
mesh_terms: D000465:Algorithms; D019380:Anti-HIV Agents / Q000494:pharmacology; D024882:Drug Resistance, Viral / Q000235:genetics*; D005838:Genotype; D015658:HIV Infections / Q000188:drug therapy / Q000453:epidemiology / Q000821:virology; D016333:HIV Protease / Q000235:genetics*; D054303:HIV Reverse Transcriptase / Q000235:genetics*; D015497:HIV-1 / Q000187:drug effects / Q000201:enzymology / Q000235:genetics*; D006801:Humans; D009154:Mutation / Q000235:genetics*
chemical_list: D019380:Anti-HIV Agents; D054303:HIV Reverse Transcriptase; D016333:HIV Protease
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