| Texto completo | |
| Autor(es): |
Busch, Jorge R.
[1]
;
Ferrari, Pablo A.
[2]
;
Flesia, Ana Georgina
[3, 4]
;
Fraiman, Ricardo
[5, 6]
;
Grynberg, Sebastian P.
[1]
;
Leonardi, Florencia
[2]
Número total de Autores: 6
|
| Afiliação do(s) autor(es): | [1] Univ Buenos Aires, Fac Ingn, Dept Matemat, RA-1053 Buenos Aires, DF - Argentina
[2] Univ Sao Paulo, Inst Matemat & Estatist, BR-05508 Sao Paulo - Brazil
[3] Consejo Nacl Invest Cient & Tecn, Ctr Invest & Estudios Matemat Cordoba, Cordoba - Argentina
[4] FAMAF UNC, Cordoba - Argentina
[5] Univ San Andres, Dept Matemat & Ciencias, Buenos Aires, DF - Argentina
[6] Univ Republica, CMAT, Montevideo - Uruguay
Número total de Afiliações: 6
|
| Tipo de documento: | Artigo Científico |
| Fonte: | Annals of Applied Statistics; v. 3, n. 2, p. 542-563, JUN 2009. |
| Citações Web of Science: | 9 |
| Resumo | |
Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. {[}Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes. (AU) | |
| Processo FAPESP: | 06/56980-0 - Filogenia e evolução de cadeias estocásticas de memória variável: aplicações ao estudo da mudança rítmica das línguas naturais e a filogenia das sequências biológicas |
| Beneficiário: | Florencia Graciela Leonardi |
| Modalidade de apoio: | Bolsas no Brasil - Pós-Doutorado |