Участник:Роман Погодин
Материал из MachineLearning.
(Новая: '''МФТИ, ФУПМ''' Кафедра '''"Интеллектуальные системы"''' Направление '''"Интеллектуальный анализ данных"''...) |
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pogodin@phystech.edu | pogodin@phystech.edu | ||
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| + | == Научно-исследовательская работа == | ||
| + | === Весна 2016, 6-й семестр === | ||
| + | "Quadratic Programming Approach to Fit Protein Complexes into Electron Density Maps", R. Pogodin, A. Katrutsa, S. Grudinin | ||
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| + | Abstract | ||
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| + | The paper investigates the problem of fitting protein complexes into electron density maps. They are represented by high-resolution cryoEM density maps converted into overlapping matrices and partly show a structure of a complex. The general purpose is to define positions of all proteins inside it. This problem is known to be NP-hard, since it lays in the field of combinatorial optimization over a set of discrete states of the complex. We introduce quadratic programming approaches to the problem. To find an approximate solution, we convert a density map into an overlapping matrix, which is generally indefinite. Since the matrix is indefinite, the optimization problem for the corresponding quadratic form is non-convex. | ||
| + | To treat non-convexity of the optimization problem, we use different convex relaxations to find which set of proteins minimizes the quadratic form best. | ||
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| + | Keywords: cryoEM; electron microscopy fitting; quadratic programming; protein structure prediction | ||
| + | Статья опубликована в трудах конференции ИТиС-2016 | ||
Версия 09:57, 7 сентября 2016
МФТИ, ФУПМ
Кафедра "Интеллектуальные системы"
Направление "Интеллектуальный анализ данных"
pogodin@phystech.edu
Научно-исследовательская работа
Весна 2016, 6-й семестр
"Quadratic Programming Approach to Fit Protein Complexes into Electron Density Maps", R. Pogodin, A. Katrutsa, S. Grudinin
Abstract
The paper investigates the problem of fitting protein complexes into electron density maps. They are represented by high-resolution cryoEM density maps converted into overlapping matrices and partly show a structure of a complex. The general purpose is to define positions of all proteins inside it. This problem is known to be NP-hard, since it lays in the field of combinatorial optimization over a set of discrete states of the complex. We introduce quadratic programming approaches to the problem. To find an approximate solution, we convert a density map into an overlapping matrix, which is generally indefinite. Since the matrix is indefinite, the optimization problem for the corresponding quadratic form is non-convex. To treat non-convexity of the optimization problem, we use different convex relaxations to find which set of proteins minimizes the quadratic form best.
Keywords: cryoEM; electron microscopy fitting; quadratic programming; protein structure prediction Статья опубликована в трудах конференции ИТиС-2016
