Name
Abstract | ||
|---|---|---|
To address one of the most challenging ecosystems issues at the cellular level, this paper surveys the fuzzy methods used in gene regulatory networks (GRNs) inference. GRNs represent causal relationships between genes that have a direct influence on the life and the development of living organisms, and provide a useful contribution to the understanding of the cellular functions as well as the mechanisms of diseases. The ecosystems impacted by GRN inference span various levels from cell to society -- globally. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2668260.2668264 | MEDES |
Keywords | Field | DocType |
algorithms,design,experimentation,big data,biology and genetics,parameter learning,fuzzy systems,measurement,gene regulatory networks,link and graph mining,theory,grn inference,heuristic methods,soft computing,performance | Data science,Data mining,Computer science,Inference,Fuzzy logic,Fuzzy control system,Soft computing,Gene regulatory network,Big data | Conference |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tuqya Al-Quzlan | 1 | 0 | 0.34 |
| Aboubekeur Hamdi-Cherif | 2 | 4 | 1.40 |
| Chafia Kara-Mohamed | 3 | 0 | 0.34 |