A gigantic amounts of data and information on molecules that constitute the very complex cell machinery have been collected, classified and stored in data banks. Although we posses enormous amount of knowledge about the properties and functions of thousands of molecular entities, we are still far from understanding how they do work in a living cell. It is clear now that these molecules (genes, proteins) are not autonomous, that there is no direct linear relation between genotype and phenotype, and that the majority of functions are carried and executed by concerted molecular activity, and that the majority of diseases are multifactorial. A basic property of the matter in a living cell (both normal and pathologic) is an interaction between variety of macromolecules, mainly proteins, genes (DNA) etc. In a process of self-organization they are able to form an active molecular biologic system – a complex, labile and dynamic network which integrity is secured by non-covalent bounds. In this essay some basic properties of network structure and the universal rules that govern them are described. Network or system biology is promising new research approach in biology and medicine.
In this paper, the author compares the of characteristics of subsystems obtained by the approximate and exact method in order to answer to the question - if the approximate method can be used to nominate the characteristics of mechatronic systems. Frequency - modal analysis has been presented for a mechanical system, i.e. transverse-vibrating clamped-free beam. Consequently, the model of the beam was presented in a five-vertex hypergraph. This model, in the case of approximate frequency-modal analysis, can be imitated in a three-vertex hypergraph. Such formulation could be the introduction to synthesis of transverse-vibrating complex beam systems with constant cross-section.
The results presented here are twofold. First, a heuristic algorithm is proposed which, through removing some unnecessary arcs from a digraph, tends to reduce it into an adjoint and thus simplifies the search for a Hamiltonian cycle. Second, a heuristic algorithm for DNA sequence assembly is proposed, which uses a graph model of the problem instance, and incorporates two independent procedures of reducing the set of arcs - one of them being the former algorithm. Finally, results of tests of the assembly algorithm on parts of chromosome arm 2R of Drosophila melanogaster are presented.