Name
Abstract | ||
|---|---|---|
Protein and DNA features extraction represents an interesting research subject for a wide range of relevant applications. In this paper, we evaluated interactions in genes and diseases by modelling them as social networks. We introduced weighted cliques to indicate patterns of those interactions and distinguish the relations between different vertices based on their strengths or levels of interactions. We used those patterns as features and evaluate their value in comparison with other feature extraction existing approaches. |
Year | Venue | Field |
|---|---|---|
2017 | IJBRA | Social network,Vertex (geometry),Biology,Pattern recognition,Feature extraction,Artificial intelligence,Bioinformatics |
DocType | Volume | Issue |
Journal | 13 | 3 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Izzat Alsmadi | 1 | 229 | 44.37 |
| Saïd Bettayeb | 2 | 83 | 9.09 |