Name
Title | ||
|---|---|---|
Developing parallel ant colonies filtered by deep learned constrains for predicting RNA secondary structure with pseudo-knots. |
Abstract | ||
|---|---|---|
•RNA secondary structure prediction is an efficient way to explore its biochemical function.•DpacoRNA is developed for precise prediction of the RNA secondary structure with pseudo-knots.•DAMpred combine deep-learned constraints with a novel PACO algorithm.•Multi-objective optimization is implemented by “parallel + filtered” mechanism to integrate the different grained objective functions.•Benchmark tests show significant advantage of the new algorithm over the state-of-the-art approaches. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.neucom.2019.12.041 | Neurocomputing |
Keywords | Field | DocType |
RNA secondary structure,Pseudo-knots,Deep learned constrains,Parallel ant colonies,Recurrent neural network | Ant colony optimization algorithms,RNA,Search algorithm,Pattern recognition,Transfer RNA,Recurrent neural network,Artificial intelligence,5S ribosomal RNA,Ant colony,Nucleic acid secondary structure,Mathematics | Journal |
Volume | ISSN | Citations |
384 | 0925-2312 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lijun Quan | 1 | 1 | 1.03 |
| Leixin Cai | 2 | 0 | 0.34 |
| Yu Chen | 3 | 1 | 1.37 |
| Jie Mei | 4 | 0 | 1.01 |
| Xiaoyu Sun | 5 | 95 | 16.54 |
| Qiang Lyu | 6 | 7 | 3.16 |