26 citations · 44 across the 6 of their papers we have counts for
6 papers
From SIR to SEAIRD: a novel data-driven modeling approach based on the Grey-box System Theory to predict the dynamics of COVID-19
Komi Midzodzi Pékpé, Djamel Zitouni, Gilles Gasso +2
Common compartmental modeling for COVID-19 is based on a priori knowledge and numerous assumptions. Additionally, they do not systematically incorporate asymptomatic cases. Our stu…
PGR: A Graph Repository of Protein 3D-Structures
Wajdi Dhifli, Abdoulaye Baniré Diallo
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 as…
ProtNN: Fast and Accurate Nearest Neighbor Protein Function Prediction based on Graph Embedding in Structural and Topological Space
Wajdi Dhifli, Abdoulaye Baniré Diallo
Studying the function of proteins is important for understanding the molecular mechanisms of life. The number of publicly available protein structures has increasingly become extre…
Toward an Efficient Multi-class Classification in an Open Universe
Wajdi Dhifli, Abdoulaye Baniré Diallo
Classification is a fundamental task in machine learning and data mining. Existing classification methods are designed to classify unknown instances within a set of previously know…
Towards an Efficient Discovery of the Topological Representative Subgraphs
Wajdi Dhifli, Mohamed Moussaoui, Rabie Saidi +1
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 tas…
Mining Representative Unsubstituted Graph Patterns Using Prior Similarity Matrix
Wajdi Dhifli, Rabie Saidi, Engelbert Mephu Nguifo
One of the most powerful techniques to study protein structures is to look for recurrent fragments (also called substructures or spatial motifs), then use them as patterns to chara…