Complex transcriptional behaviours are encoded in the DNA sequences of gene regulatory regions. Advances in our understanding of these behaviours have been recently gained through quantitative models that describe how molecules such as transcription factors and nucleosomes interact with genomic sequences. An emerging view is that every regulatory sequence is associated with a unique binding affinity landscape for each molecule and, consequently, with a unique set of molecule-binding configurations and transcriptional outputs. We present a quantitative framework based on existing methods that unifies these ideas. This framework explains many experimental observations regarding the binding patterns of factors and nucleosomes and the dynamics of transcriptional activation. It can also be used to model more complex phenomena such as transcriptional noise and the evolution of transcriptional regulation.

At the very moment we can see development in Iran, that in the future may be called "Internet revolution", "Facebook revolution" or "Social networks revolution".

A state does not have power in isolation from others without considering its linked interactions to others nor from system structure without considering its structural positions in the system; rather, it has power as a consequence of its interactive relations with other states in the system and its structural positions in the networks of relations. This paper proposes a new power concept, using the social network perspective, called "structural network power," defined as the power of an individual state arising from its location within the networks of international relations. Adapting this new network power concept, this paper also assembles and provides the data on the new measure of national power (SNPI, Structural Network Power Index) 1950-2000 for all states existing in the international system.