- Title
- DFS based partial pathways in GA for protein structure prediction
- Creator
- Hoque, Md Tamjidul; Chetty, Madhu; Lewis, Andrew; Sattar, Abdul
- Date
- 2008
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/58271
- Identifier
- vital:5946
- Identifier
-
https://doi.org/10.1007/978-3-540-88436-1_4
- Abstract
- Nondeterministic conformational search techniques, such as Genetic Algorithms (GAs) are promising for solving protein structure prediction (PSP) problem. The crossover operator of a GA can underpin the formation of potential conformations by exchanging and sharing potential sub-conformations, which is promising for solving PSP. However, the usual nature of an optimum PSP conformation being compact can produce many invalid conformations (by having non-self-avoiding-walk) using crossover. While a crossover-based converging conformation suffers from limited pathways, combining it with depth-first search (DFS) can partially reveal potential pathways. DFS generates random conformations increasingly quickly with increasing length of the protein sequences compared to random-move-only-based conformation generation. Random conformations are frequently applied for maintaining diversity as well as for initialization in many GA variations.
- Publisher
- Melbourne Springer
- Relation
- Third IAPR International Conference, PRIB 2008
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0801 Artificial Intelligence and Image Processing
- Full Text
- Reviewed
- Hits: 1280
- Visitors: 1372
- Downloads: 106
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE2 | Accepted version | 569 KB | Adobe Acrobat PDF | View Details Download |