Soft computing methods for the prediction of protein tertiary structures: A survey
The problem of protein structure prediction (PSP) represents one of the most important challenges in computational biology. Determining the three dimensional structure of proteins is necessary to under stand their functions at molecular level. The most representative soft computing approaches for so...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión enviada para evaluación y publicación |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/133555 |
| Acceso en línea: | https://hdl.handle.net/11441/133555 https://doi.org/10.1016/j.asoc.2015.06.024 |
| Access Level: | acceso abierto |
| Palabra clave: | Protein structure prediction Soft computing Protein contact map Support vector machines Neural networks Evolutionary algorithms |
| Sumario: | The problem of protein structure prediction (PSP) represents one of the most important challenges in computational biology. Determining the three dimensional structure of proteins is necessary to under stand their functions at molecular level. The most representative soft computing approaches for solving the protein tertiary structure prediction problem are summarized in this paper. These approaches have been categorized following the type of methodology. A total of 90 relevant works published in last 15 years in the field of protein structure prediction have been reported, including the best competitors in last CASP editions. However, despite large research effort in last decades, a considerable scope for further improvement still remains in this area. |
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