Inherent size constraints on prokaryote gene networks due to "accelerating" growth.

Networks exhibiting "accelerating" growth have total link numbers growing faster than linearly with network size and either reach a limit or exhibit graduated transitions from nonstationary-to-stationary statistics and from random to scale-free to regular statistics as the network size grows. However, if for any reason the network cannot tolerate such gross structural changes then accelerating networks are constrained to have sizes below some critical value. This is of interest as the regulatory gene networks of single-celled prokaryotes are characterized by an accelerating quadratic growth and are size constrained to be less than about 10,000 genes encoded in DNA sequence of less than about 10 megabases.

Accelerating, hyperaccelerating, and decelerating networks.

Many growing networks possess accelerating statistics where the number of links added with each new node is an increasing function of network size so the total number of links increases faster than linearly with network size. In particular, biological networks can display a quadratic growth in regulator number with genome size even while remaining sparsely connected. These features are mutually incompatible in standard treatments of network theory which typically require that every new network node possesses at least one connection.

The evolution of controlled multitasked gene networks: the role of introns and other noncoding RNAs in the development of complex organisms.

Eukaryotic phenotypic diversity arises from multitasking of a core proteome of limited size. Multitasking is routine in computers, as well as in other sophisticated information systems, and requires multiple inputs and outputs to control and integrate network activity. Higher eukaryotes have a mosaic gene structure with a dual output, mRNA (protein-coding) sequences and introns, which are released from the pre-mRNA by posttranscriptional processing.

Information processing in multigame environments modeling the evolution of sex via punctuated equilibria.

Uncertain environments are properly described by probability distributions which, as usual, can be collapsed or conditioned into distributions with reduced uncertainty through the processing of environmental information. Organisms which force this collapse gain evolutionary advantage by being able to employ strategies in a known environment rather than in a merely probable one. The accrued benefit gained from processing information can be precisely quantified by comparing benefits returned using distributions prior to, and after collapse, and these often large and immediate benefits can amply justify the evolutionary cost of information processing systems.