Euclidean distance geometry and applications
Euclidean distance geometry is the study of Euclidean geometry based on the concept of
distance. This is useful in several applications where the input data consist of an incomplete …
distance. This is useful in several applications where the input data consist of an incomplete …
Recent advances on the discretizable molecular distance geometry problem
The Molecular Distance Geometry Problem (MDGP) consists in finding an embedding in R3
of a nonnegatively weighted simple undirected graph with the property that the Euclidean …
of a nonnegatively weighted simple undirected graph with the property that the Euclidean …
[HTML][HTML] Fisher information distance: A geometrical reading
SIR Costa, SA Santos, JE Strapasson - Discrete Applied Mathematics, 2015 - Elsevier
This paper presents a geometrical approach to the Fisher distance, which is a measure of
dissimilarity between two probability distribution functions. The Fisher distance, as well as …
dissimilarity between two probability distribution functions. The Fisher distance, as well as …
Recent advances on the interval distance geometry problem
We discuss a discretization-based solution approach for a classic problem in global
optimization, namely the distance geometry problem (DGP). We focus our attention on a …
optimization, namely the distance geometry problem (DGP). We focus our attention on a …
DiG-Park: a smart parking availability searching method using V2V/V2I and DGP-class problem
Localization systems for outdoor areas using GNSS based systems (like GPS, GLONASS
and more) are nowadays widespread and commonly-available in devices like smartphones …
and more) are nowadays widespread and commonly-available in devices like smartphones …
Distance geometry and data science
L Liberti - Top, 2020 - Springer
Data are often represented as graphs. Many common tasks in data science are based on
distances between entities. While some data science methodologies natively take graphs as …
distances between entities. While some data science methodologies natively take graphs as …
Systematic exploration of protein conformational space using a distance geometry approach
The optimization approaches classically used during the determination of protein structure
encounter various difficulties, especially when the size of the conformational space is large …
encounter various difficulties, especially when the size of the conformational space is large …
[HTML][HTML] Discretization vertex orders in distance geometry
When a weighted graph is an instance of the Distance Geometry Problem (DGP), certain
types of vertex orders (called discretization orders) allow the use of a very efficient, precise …
types of vertex orders (called discretization orders) allow the use of a very efficient, precise …
An algorithm to enumerate all possible protein conformations verifying a set of distance constraints
Background The determination of protein structures satisfying distance constraints is an
important problem in structural biology. Whereas the most common method currently …
important problem in structural biology. Whereas the most common method currently …
Low-resolution description of the conformational space for intrinsically disordered proteins
Intrinsically disordered proteins (IDP) are at the center of numerous biological processes,
and attract consequently extreme interest in structural biology. Numerous approaches have …
and attract consequently extreme interest in structural biology. Numerous approaches have …