Участник:Andrey Ryazanov
Материал из MachineLearning.
| Строка 9: | Строка 9: | ||
andrei.ryazanov@phystech.edu | andrei.ryazanov@phystech.edu | ||
| - | = | + | = Отчет о научно-исследовательской работе = |
== Задача обратного фолдинга белка == | == Задача обратного фолдинга белка == | ||
| - | ''' | + | |
| - | Ryazanov A., Karasikov M., Grudinin S. Inverse Protein Folding Problem via Quadratic Programming, | + | |
| + | === Весна 2016, 16-й семестр === | ||
| + | '''Inverse Protein Folding Problem via Quadratic Prgramming''', Рязанов А. В., Карасиков М. Е., Грудинин С. В. | ||
| + | This paper presents a method of reconstruction a primary structure of a protein that folds into a given geometrical shape. This method predicts the primary structure of a protein and restores its linear sequence of amino acids in the polypeptide chain using the tertiary structure of a molecule. Unknown amino acids are determined according to the principle of energy minimization. This study represents inverse folding problem as a quadratic optimization problem and uses different relaxation techniques to reduce it to the problem of convex optimizations. Computational experiment compares the quality of these approaches on real protein structures. | ||
| + | '''Публикация''': | ||
| + | Ryazanov A., Karasikov M., Grudinin S. Inverse Protein Folding Problem via Quadratic Programming, принята к публикации в сборнике трудов конференции ИТиС 2016. | ||
'''Доклады''': | '''Доклады''': | ||
Версия 10:52, 19 сентября 2016
Рязанов Андрей Владимирович
МФТИ, ФУПМ
Кафедра "Интеллектуальные системы"
Направление "Интеллектуальный анализ данных"
andrei.ryazanov@phystech.edu
Отчет о научно-исследовательской работе
Задача обратного фолдинга белка
Весна 2016, 16-й семестр
Inverse Protein Folding Problem via Quadratic Prgramming, Рязанов А. В., Карасиков М. Е., Грудинин С. В. This paper presents a method of reconstruction a primary structure of a protein that folds into a given geometrical shape. This method predicts the primary structure of a protein and restores its linear sequence of amino acids in the polypeptide chain using the tertiary structure of a molecule. Unknown amino acids are determined according to the principle of energy minimization. This study represents inverse folding problem as a quadratic optimization problem and uses different relaxation techniques to reduce it to the problem of convex optimizations. Computational experiment compares the quality of these approaches on real protein structures. Публикация: Ryazanov A., Karasikov M., Grudinin S. Inverse Protein Folding Problem via Quadratic Programming, принята к публикации в сборнике трудов конференции ИТиС 2016.
Доклады: Ryazanov A., Karasikov M., Grudinin S. Inverse Protein Folding Problem via Quadratic Programming, Традиционная молодежная Школа "Управления, информация и оптимизация".
Гранты: РФФИ 16-37-00111
