- Title
- Conflict resolution based global search operators for long protein structures prediction
- Creator
- Islam, Md; Chetty, Madhu; Murshed, Manzur
- Date
- 2011
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/157250
- Identifier
- vital:11543
- Identifier
-
https://doi.org/10.1007/978-3-642-24955-6_75
- Identifier
- ISBN:978-364224954-9
- Abstract
- Most population based evolutionary algorithms (EAs) have struggled to accurately predict structure for long protein sequences. This is because conventional operators, i.e., crossover and mutation, cannot satisfy constraints (e.g., connected chain and self-avoiding-walk) of the complex combinatorial multi-modal problem, protein structure prediction (PSP). In this paper, we present novel crossover and mutation operators based on conflict resolution for handling long protein sequences in PSP using lattice models. To our knowledge, this is a pioneering work to address the PSP limitations for long sequences. Experiments carried out with long PDB sequences show the effectiveness of the proposed method. © 2011 Springer-Verlag.
- Publisher
- Springer
- Relation
- 18th International Conference on Neural Information Processing, ICONIP 2011; Shanghai; China; 13th to 17th November 2011; published in Neural Information Processing, (Lecture Notes in Computer Science series) Vol. 7062 (1) p.636-645
- Rights
- Copyright Springer
- Rights
- This metadata is freely available under a CCO license
- Subject
- Clustered memetic algorithm; Conflict Resolution; Crossover and mutation; Global search; Lattice model; Memetic algorithms; Multimodal problems; Protein sequence; Protein structure prediction; Protein structures
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