47 research outputs found
Memory functions and Correlations in Additive Binary Markov Chains
A theory of additive Markov chains with long-range memory, proposed earlier
in Phys. Rev. E 68, 06117 (2003), is developed and used to describe statistical
properties of long-range correlated systems. The convenient characteristics of
such systems, a memory function, and its relation to the correlation properties
of the systems are examined. Various methods for finding the memory function
via the correlation function are proposed. The inverse problem (calculation of
the correlation function by means of the prescribed memory function) is also
solved. This is demonstrated for the analytically solvable model of the system
with a step-wise memory function.Comment: 11 pages, 5 figure
Superimposé: a 3D structural superposition server
The Superimposé webserver performs structural similarity searches with a preference towards 3D structure-based methods. Similarities can be detected between small molecules (e.g. drugs), parts of large structures (e.g. binding sites of proteins) and entire proteins. For this purpose, a number of algorithms were implemented and various databases are provided. Superimposé assists the user regarding the selection of a suitable combination of algorithm and database. After the computation on our server infrastructure, a visual assessment of the results is provided. The structure-based in silico screening for similar drug-like compounds enables the detection of scaffold-hoppers with putatively similar effects. The possibility to find similar binding sites can be of special interest in the functional analysis of proteins. The search for structurally similar proteins allows the detection of similar folds with different backbone topology. The Superimposé server is available at: http://bioinformatics.charite.de/superimpose
Congestion in a macroscopic model of self-driven particles modeling gregariousness
International audienceWe analyze a macroscopic model with a maximal density constraint which describes short range repulsion in biological systems. This system aims at modeling finite-size particles which cannot overlap and repel each other when they are too close. The parts of the fluid where the maximal density is reached behave like incompressible fluids while lower density regions are compressible. This paper investigates the transition between the compressible and incompressible regions. To capture this transition, we study a one-dimensional Riemann problem and introduce a perturbation problem which regularizes the compressible-incompressible transition. Specific difficulties related to the non-conservativity of the problem are discussed