<p>Distance matrices are calculated from <i>N</i> related PDB entries in form of Cartesian coordinates. The lower triangles of the distance matrices are assembled into columns of matrix <b>A</b>. The first a few significant left singular vectors in <b>U</b> resulting from SVD are reconstructed to form decomposed lower triangles. The corresponding singular values and right singular vectors are presented in a multidimensional conformational space. Any given location in this space leads to a recomposed lower triangle by a linear combination of the significant lower triangles. Finally, a hypothetical structure is determined by distance geometry using all constraints in the recomposed lower triangle.</p
A distance geometry based protein modelling algorithm is presented which relies on the projection of...
In the practice of information extraction, the input data are usually arranged into pattern matrices...
BackgoundUnknown protein structures can be predicted from known structures (the scaffolds) with sequ...
<p>α and β are in warm and cool colors, respectively. Quaternary T state is in light pink and light...
Asymmetric relationships contained in square data matrices like proximities (e.g. similarity ratings...
We construct a weighted Euclidean distance that approximates any distance or dissimilarity measure b...
The statistical shape analysis called Procrustes analysis minimizes the Frobenius distance between m...
Similarity between patterns is commonly used in many distance-based classification algorithms like K...
This book offers a comprehensive and accessible exposition of Euclidean Distance Matrices (EDMs) and...
Dimensionality reduction is the process by which a set of data points in a higher dimensional space ...
The concept of distance is a fundamental notion that forms a basis for the orientation in space. It ...
Multiblock analysis attacks the problem of how to combine data from various data sources for purpose...
International audienceIn 1997, A. Barvinok gave a probabilistic algorithm to derive a near-feasible ...
We introduce a novel statistical concept, called a supervised distance matrix, which quantifies pair...
Summary: We introduce a novel unsupervised approach for the organization and visualization of multid...
A distance geometry based protein modelling algorithm is presented which relies on the projection of...
In the practice of information extraction, the input data are usually arranged into pattern matrices...
BackgoundUnknown protein structures can be predicted from known structures (the scaffolds) with sequ...
<p>α and β are in warm and cool colors, respectively. Quaternary T state is in light pink and light...
Asymmetric relationships contained in square data matrices like proximities (e.g. similarity ratings...
We construct a weighted Euclidean distance that approximates any distance or dissimilarity measure b...
The statistical shape analysis called Procrustes analysis minimizes the Frobenius distance between m...
Similarity between patterns is commonly used in many distance-based classification algorithms like K...
This book offers a comprehensive and accessible exposition of Euclidean Distance Matrices (EDMs) and...
Dimensionality reduction is the process by which a set of data points in a higher dimensional space ...
The concept of distance is a fundamental notion that forms a basis for the orientation in space. It ...
Multiblock analysis attacks the problem of how to combine data from various data sources for purpose...
International audienceIn 1997, A. Barvinok gave a probabilistic algorithm to derive a near-feasible ...
We introduce a novel statistical concept, called a supervised distance matrix, which quantifies pair...
Summary: We introduce a novel unsupervised approach for the organization and visualization of multid...
A distance geometry based protein modelling algorithm is presented which relies on the projection of...
In the practice of information extraction, the input data are usually arranged into pattern matrices...
BackgoundUnknown protein structures can be predicted from known structures (the scaffolds) with sequ...