Efficient conformational space exploration in ab initioprotein folding simulation
dc.contributor.author | Ullah, Ahammed | en_US |
dc.date.accessioned | 2016-10-11T05:37:47Z | |
dc.date.available | 2016-10-11T05:37:47Z | |
dc.date.issued | 2015 | en_US |
dc.identifier.other | HPU4160586 | en_US |
dc.identifier.uri | https://lib.hpu.edu.vn/handle/123456789/23667 | en_US |
dc.description.abstract | Ab initio protein folding simulation largely depends on knowledge-based energy functions that are derived from known protein structures using statistical methods. These knowledge-based energy functions provide us with a good approximation of real protein energetics. However, these energy functions are not very informative for search algorithms and fail to distinguish the types of amino acid interactions that contribute largely to the energy function from those that do not. As a result, search algorithms frequently get trapped into the local minima | en_US |
dc.format.extent | 21 p. | en_US |
dc.format.mimetype | application/pdf | en_US |
dc.language.iso | en | en_US |
dc.subject | Computer science | en_US |
dc.subject | Bioinformatics | en_US |
dc.subject | Computational biology | en_US |
dc.subject | Artificial intelligence | en_US |
dc.subject | Protein structure prediction | en_US |
dc.title | Efficient conformational space exploration in ab initioprotein folding simulation | en_US |
dc.type | Article | en_US |
dc.size | 822KB | en_US |
dc.department | Education | en_US |
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