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» Predicting Peroxisomal Proteins
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BMCBI
2010
150views more  BMCBI 2010»
13 years 8 months ago
Automatic structure classification of small proteins using random forest
Background: Random forest, an ensemble based supervised machine learning algorithm, is used to predict the SCOP structural classification for a target structure, based on the simi...
Pooja Jain, Jonathan D. Hirst
BMCBI
2008
200views more  BMCBI 2008»
13 years 8 months ago
Defining functional distances over Gene Ontology
Background: A fundamental problem when trying to define the functional relationships between proteins is the difficulty in quantifying functional similarities, even when well-stru...
Angela del Pozo, Florencio Pazos, Alfonso Valencia
BMCBI
2008
98views more  BMCBI 2008»
13 years 8 months ago
PredGPI: a GPI-anchor predictor
Background: Several eukaryotic proteins associated to the extracellular leaflet of the plasma membrane carry a Glycosylphosphatidylinositol (GPI) anchor, which is linked to the C-...
Andrea Pierleoni, Pier Luigi Martelli, Rita Casadi...
BMCBI
2007
106views more  BMCBI 2007»
13 years 8 months ago
Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive as
Background: A widely-used approach for discovering functional and physical interactions among proteins involves phylogenetic profile comparisons (PPCs). Here, proteins with simila...
Raja Jothi, Teresa M. Przytycka, L. Aravind
ISMB
1994
13 years 9 months ago
Stochastic Motif Extraction Using Hidden Markov Model
In this paper, westudy the application of an ttMM(hidden Markov model) to the problem of representing protein sequencesby a stochastic motif. Astochastic protein motif represents ...
Yukiko Fujiwara, Minoru Asogawa, Akihiko Konagaya