The three-dimensional shape of a protein plays a key role in determining its function, so proteins in which particular atoms have very similar configurations in space often have similar functions. There is therefore a need for efficient methodology to identify, given two or more proteins represented by the coordinates of their atoms, subsets of those atoms which match within measurement error, after allowing for appropriate geometrical transformations to align the proteins. This chapter describes a Bayesian model-based methodology for such tasks, and presents several challenging applications.
Motivation: Large-scale conformational changes in proteins are implicated in many important biologic...
We describe a method for aligning multiple unlabeled configurations simultane- ously. Specifically, ...
We apply Hidden Markov Models (HMMs) to the problem of statistical modeling and multiple alignment o...
An important problem in shape analysis is to match configurations of points in space after filtering...
We develop a Bayesian model for the alignment of two point configurations under the full similarity ...
© 2015 John Wiley & Sons, Ltd. All rights reserved. Professor Kanti Mardia has made numerous origina...
An important problem in shape analysis is to match configurations of points in space filtering out s...
In this Thesis we explore the problem of structural alignment of protein molecules using statistical...
The availability of three-dimensional spatial information about protein structures is expanding, as ...
Abstract Background Matching functional sites is a key problem for the understanding of protein func...
In drug design one attempts to correlate the three–dimensional structure of drug molecules with thei...
We explore how ideas and practices common in Bayesian modeling can be applied to help assess the qua...
Methods developed in the statistical theory of shape provide a natural approach to mod-eling variabi...
In matching active sites of proteins, we may assume that we are given the 3-D atomic con-figuration ...
A novel approach for structure alignment is presented, where the key ingredients are: (1) An error f...
Motivation: Large-scale conformational changes in proteins are implicated in many important biologic...
We describe a method for aligning multiple unlabeled configurations simultane- ously. Specifically, ...
We apply Hidden Markov Models (HMMs) to the problem of statistical modeling and multiple alignment o...
An important problem in shape analysis is to match configurations of points in space after filtering...
We develop a Bayesian model for the alignment of two point configurations under the full similarity ...
© 2015 John Wiley & Sons, Ltd. All rights reserved. Professor Kanti Mardia has made numerous origina...
An important problem in shape analysis is to match configurations of points in space filtering out s...
In this Thesis we explore the problem of structural alignment of protein molecules using statistical...
The availability of three-dimensional spatial information about protein structures is expanding, as ...
Abstract Background Matching functional sites is a key problem for the understanding of protein func...
In drug design one attempts to correlate the three–dimensional structure of drug molecules with thei...
We explore how ideas and practices common in Bayesian modeling can be applied to help assess the qua...
Methods developed in the statistical theory of shape provide a natural approach to mod-eling variabi...
In matching active sites of proteins, we may assume that we are given the 3-D atomic con-figuration ...
A novel approach for structure alignment is presented, where the key ingredients are: (1) An error f...
Motivation: Large-scale conformational changes in proteins are implicated in many important biologic...
We describe a method for aligning multiple unlabeled configurations simultane- ously. Specifically, ...
We apply Hidden Markov Models (HMMs) to the problem of statistical modeling and multiple alignment o...