Predicting the function of a protein from its sequence is typically addressed using sequence-similarity. Here we propose a motif-based approach, using supervised motif extraction from protein sequences belonging to one functional family. The resulting deterministic motifs form Common Peptides (CPs) that characterize this family, allow for data mining of its proteins and facilitate further partition of the family into cluster
Discrete motifs that discriminate functional classes of proteins are useful for classifying new sequ...
Identifying shared sequence segments along amino acid sequences generally requires a collection of c...
We describe a method for discovering active motifs in a set of related protein sequences. The method...
We use methods from Data Mining and Knowledge Discovery to design an algorithm for detecting motifs ...
This thesis describes an approach to data-driven discovery of decision trees or rules for assigning ...
[[abstract]]Protein motifs, which are specific regions and conserved regions, are found by comparing...
Thesis (Ph. D.)--University of Washington, 2002We introduce CASTOR, an automatic, unsupervised syste...
Abstract: Protein motifs, which are specific regions and conserved regions, are found by comparing m...
Background: In protein sequence classification, identification of the sequence motifs or n-grams tha...
www.cs.iastate.edu/~honavar/aigroup.html This paper describes an approach to data-driven discovery o...
Protein sequence motifs are gathering more and more attention in the field of sequence analysis. Th...
Summary. Protein function prediction, i.e. classification of protein sequences according to their bi...
We use methods from data mining and knowledge discovery to design an algorithm for detecting motifs ...
We introduce an unsupervised method for extracting meaningful motifs from biological sequence data. ...
Proteins can be grouped into families according to their biological functions. This paper presents a...
Discrete motifs that discriminate functional classes of proteins are useful for classifying new sequ...
Identifying shared sequence segments along amino acid sequences generally requires a collection of c...
We describe a method for discovering active motifs in a set of related protein sequences. The method...
We use methods from Data Mining and Knowledge Discovery to design an algorithm for detecting motifs ...
This thesis describes an approach to data-driven discovery of decision trees or rules for assigning ...
[[abstract]]Protein motifs, which are specific regions and conserved regions, are found by comparing...
Thesis (Ph. D.)--University of Washington, 2002We introduce CASTOR, an automatic, unsupervised syste...
Abstract: Protein motifs, which are specific regions and conserved regions, are found by comparing m...
Background: In protein sequence classification, identification of the sequence motifs or n-grams tha...
www.cs.iastate.edu/~honavar/aigroup.html This paper describes an approach to data-driven discovery o...
Protein sequence motifs are gathering more and more attention in the field of sequence analysis. Th...
Summary. Protein function prediction, i.e. classification of protein sequences according to their bi...
We use methods from data mining and knowledge discovery to design an algorithm for detecting motifs ...
We introduce an unsupervised method for extracting meaningful motifs from biological sequence data. ...
Proteins can be grouped into families according to their biological functions. This paper presents a...
Discrete motifs that discriminate functional classes of proteins are useful for classifying new sequ...
Identifying shared sequence segments along amino acid sequences generally requires a collection of c...
We describe a method for discovering active motifs in a set of related protein sequences. The method...