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 …

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 …

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 …

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 …

Localization systems for outdoor areas using GNSS based systems (like GPS, GLONASS
and more) are nowadays widespread and commonly-available in devices like smartphones …

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 …

The optimization approaches classically used during the determination of protein structure
encounter various difficulties, especially when the size of the conformational space is large …

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 …

Background The determination of protein structures satisfying distance constraints is an
important problem in structural biology. Whereas the most common method currently …

Intrinsically disordered proteins (IDP) are at the center of numerous biological processes,
and attract consequently extreme interest in structural biology. Numerous approaches have …