| 1. Identificação | |
| Tipo de Referência | Artigo em Revista Científica (Journal Article) |
| Site | plutao.sid.inpe.br |
| Código do Detentor | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identificador | J8LNKAN8RW/39RQ99C |
| Repositório | dpi.inpe.br/plutao/2011/06.11.02.31.49 |
| Última Atualização | 2011:10.18.13.45.38 (UTC) administrator |
| Repositório de Metadados | dpi.inpe.br/plutao/2011/06.11.02.31.50 |
| Última Atualização dos Metadados | 2018:06.05.00.01.16 (UTC) administrator |
| Chave Secundária | INPE--PRE/ |
| DOI | 10.1371/journal.pcbi.1001131 |
| ISSN | 1553-734X |
| Rótulo | lattes: 9147853693310634 11 ANDRADERSSDLGPEOS:2011:ApPhAn |
| Chave de Citação | AndradeRSSLGPEO:2011:ApPhAn |
| Título | Detecting Network Communities: An Application to Phylogenetic Analysis  |
| Ano | 2011 |
| Data de Acesso | 17 maio 2024 |
| Tipo Secundário | PRE PI |
| Número de Arquivos | 1 |
| Tamanho | 222 KiB |
| 2. Contextualização | |
| Autor | 1 Andrade, Roberto F. S. 2 Rocha-Neto, Ivan C. 3 Santos, Leonardo B. L. 4 Santana, Charles N. 5 Lobão, Thierry Petit 6 Goés-Neto, Aristóteles 7 Pinho, Suani T. R. 8 El-Hani, Charbel N. 9 Ouzounis, Christos |
| Grupo | 1 2 3 LAC-CTE-INPE-MCT-BR 4 CTE-CTE-INPE-MCT-BR |
| Afiliação | 1 Institute of Physics, Federal University of Bahia, Campus Universitário de Ondina, Salvador, Bahia, Brazil 2 Institute of Mathematics, Federal University of Bahia, Campus Universitário de Ondina, Salvador, Bahia, Brazil 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Instituto Nacional de Pesquisas Espaciais (INPE), Mediterranean Institute of Advanced Studies, IMEDEA (CSIC-UIB), Esporles (Islas Baleares), Spain 5 nstitute of Mathematics, Federal University of Bahia, Campus Universitário de Ondina, Salvador, Bahia, Brazil 6 Department of Biological Sciences, State University of Feira de Santana, Feira de Santana, Bahia, Brazil 7 Institute of Physics, Federal University of Bahia, Campus Universitário de Ondina, Salvador, Bahia, Brazil 8 Institute of Biology, Federal University of Bahia, Campus Universitário de Ondina, Salvador, Bahia, Brazil |
| Endereço de e-Mail | santoslbl@gmail.com |
| Revista | PLoS Computational Biology |
| Volume | 7 |
| Páginas | e1001131 |
| Nota Secundária | A2_ASTRONOMIA_/_FÍSICA A1_CIÊNCIAS_BIOLÓGICAS_II C_ENSINO_DE_CIÊNCIAS_E_MATEMATICA B2_SAÚDE_COLETIVA |
| Histórico (UTC) | 2011-06-11 17:43:42 :: lattes -> marciana :: 2011 2011-10-18 13:45:38 :: marciana -> administrator :: 2011 2018-06-05 00:01:16 :: administrator -> marciana :: 2011 |
| 3. Conteúdo e estrutura | |
| É a matriz ou uma cópia? | é a matriz |
| Estágio do Conteúdo | concluido |
| Transferível | 1 |
| Tipo do Conteúdo | External Contribution |
| Tipo de Versão | publisher |
| Resumo | This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used for network construction so that the network structure can be analyzed to recover phylogenetically useful information from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks, explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix . The most relevant networks are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (>70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100 organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance, likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis. Author Summary Top Complex weighted networks have been applied to uncover organizing principles of complex biological, technological, and social systems. We propose herein a new method to identify communities in such structures and apply it to phylogenetic analysis. Recent studies using this theory in genomics and proteomics contributed to the understanding of the structure and dynamics of cellular complex interaction webs. Three main distinct molecular networks have been investigated based on transcriptional and metabolic activity, and on protein interaction. Here we consider the evolutionary relationship between proteins throughout phylogeny, employing the complex network approach to perform a comparative study of the enzymes related to the chitin metabolic pathway. We show how the similarity index of protein sequences can be used for network construction, and how the underlying structure is analyzed by the computational routines of our method to recover useful and sound information for phylogenetic studies. By focusing on the modular character of protein similarity networks, we were successful in matching the identified networks modules to main bacterial phyla, and even some bacterial classes. The network-based method reported here can be used as a new powerful tool for identifying communities in complex networks, retrieving useful information for phylogenetic studies. |
| Área | COMP |
| Arranjo 1 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Detecting Network Communities:... |
| Arranjo 2 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > COCTE > Detecting Network Communities:... |
| Conteúdo da Pasta doc | acessar |
| Conteúdo da Pasta source | não têm arquivos |
| Conteúdo da Pasta agreement | não têm arquivos |
| 4. Condições de acesso e uso | |
| URL dos dados | http://urlib.net/ibi/J8LNKAN8RW/39RQ99C |
| URL dos dados zipados | http://urlib.net/zip/J8LNKAN8RW/39RQ99C |
| Idioma | en |
| Arquivo Alvo | info doi_10.1371_journal.pcbi.1001131.htm |
| Grupo de Usuários | administrator lattes marciana |
| Visibilidade | shown |
| Política de Arquivamento | allowpublisher allowfinaldraft |
| Permissão de Leitura | allow from all |
| Permissão de Atualização | não transferida |
| 5. Fontes relacionadas | |
| Unidades Imediatamente Superiores | 8JMKD3MGPCW/3ESGTTP 8JMKD3MGPCW/3ET76KE |
| Divulgação | WEBSCI; PORTALCAPES. |
| Acervo Hospedeiro | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
| 6. Notas | |
| Campos Vazios | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel electronicmailaddress format isbn keywords lineage mark mirrorrepository month nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup resumeid rightsholder schedulinginformation secondarydate session shorttitle sponsor subject tertiarymark tertiarytype typeofwork url |
| 7. Controle da descrição | |
| e-Mail (login) | marciana |
| atualizar | |