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Conflict Resolution Based Global Search Operators for Long Protein Structures Prediction

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Book cover Neural Information Processing (ICONIP 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7062))

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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.

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Islam, M.K., Chetty, M., Murshed, M. (2011). Conflict Resolution Based Global Search Operators for Long Protein Structures Prediction. In: Lu, BL., Zhang, L., Kwok, J. (eds) Neural Information Processing. ICONIP 2011. Lecture Notes in Computer Science, vol 7062. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24955-6_75

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  • DOI: https://doi.org/10.1007/978-3-642-24955-6_75

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24954-9

  • Online ISBN: 978-3-642-24955-6

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