The family based variability in protein family expansion.
SARKAR, Anasua
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Models and Algorithms for the Genome [MAGNOME]
Department of Information Technology [GCELT]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Models and Algorithms for the Genome [MAGNOME]
Department of Information Technology [GCELT]
DURRENS, Pascal
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Models and Algorithms for the Genome [MAGNOME]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Models and Algorithms for the Genome [MAGNOME]
SARKAR, Anasua
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Models and Algorithms for the Genome [MAGNOME]
Department of Information Technology [GCELT]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Models and Algorithms for the Genome [MAGNOME]
Department of Information Technology [GCELT]
DURRENS, Pascal
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Models and Algorithms for the Genome [MAGNOME]
< Reduce
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Models and Algorithms for the Genome [MAGNOME]
Language
en
Article de revue
This item was published in
International Journal of Bioinformatics Research and Applications. 2013, vol. 9, n° 2, p. 121-33
Inderscience
English Abstract
In this paper we propose an automatic protein family expansion approach for recruitment of new members among the protein-coding genes in newly sequenced genomes. The criteria for adding a new member to a family depends on ...Read more >
In this paper we propose an automatic protein family expansion approach for recruitment of new members among the protein-coding genes in newly sequenced genomes. The criteria for adding a new member to a family depends on the structure of each individual family versus being globally uniform. The detection of a threshold in the ROC space of all sorted iterative profile sets defines the alignments selection criteria for each family. Furthermore, the statistical estimation of most-frequent optimal sorting criteria generates the optimal filtering strategy in a learning-parameter set for profile-based homology search.Read less <
English Keywords
protein family expansion
sequence profiles
protein specific scoring matrix
remote homologues
ROC analysis
alignment selection criteria
optimal filtering strategy
proteins
protein families
bioinformatics
gene sequences
Origin
Hal imported