Wajdi Dhifli

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One of the most powerful techniques to study proteins is to look for recurrent fragments (also called substructures), then use them as patterns to characterize the proteins under study. Although protein sequences have been extensively studied in the literature, studying protein three-dimensional (3D) structures can reveal relevant structural and functional(More)
One of the most powerful techniques to study protein structures is to look for recurrent fragments (also called substruc-tures or spatial motifs), then use them as patterns to characterize the proteins under study. An emergent trend consists in parsing proteins three-dimensional (3D) structures into graphs of amino acids. Hence, the search of recurrent(More)
Graph theory and graph mining constitute rich fields of computational techniques to study the structures, topologies and properties of graphs. These techniques constitute a good asset in bioinformatics if there exist efficient methods for transforming biological data into graphs. In this paper, we present Protein Graph Repository (PGR), a novel database of(More)
Studying the functions and structures of proteins is important for understanding the molecular mechanisms of life. The number of publicly available protein structures has increasingly become extremely large. Still, the classification of a protein structure remains a difficult, costly, and time consuming task. The difficulties are often due to the essential(More)
✐ ✐ " main " — 2016/1/26 — 1:28 — page 1 — #1 Abstract Motivation: Studying the function of proteins is important for understanding the molecular mechanisms of life. The number of publicly available protein structures has increasingly become extremely large. Still, the determination of the function of a protein structure remains a difficult, costly, and(More)
Classification is a fundamental task in machine learning and artificial intelligence. Existing classification methods are designed to classify unknown instances within a set of previously known classes that are seen in training. Such classification takes the form of prediction within a closed-set. However, a more realistic scenario that fits the ground(More)
With the emergence of graph databases, the task of frequent subgraph discovery has been extensively addressed. Although the proposed approaches in the literature have made this task feasible, the number of discovered frequent subgraphs is still very high to be efficiently used in any further exploration. Feature selection based on exact or approximate(More)
One of the used techniques to address protein structure investigation is to look for recurrent fragments (also called substructures or spatial motifs), then use these spatial motifs as patterns to characterize the proteins under consideration. An emergent trend consists on parsing proteins into graphs of amino acids. Hence, the search of recurrent spatial(More)
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