PMID- 16306387
OWN - NLM
STAT- MEDLINE
DCOM- 20070905
LR  - 20130520
IS  - 1367-4811 (Electronic)
IS  - 1367-4803 (Linking)
VI  - 21 Suppl 3
DP  - 2005 Nov 1
TI  - Modeling genome evolution with a diffusion approximation of a birth-and-death 
      process.
PG  - iii12-9
AB  - MOTIVATION: In our previous studies, we developed discrete-space birth, death and 
      innovation models (BDIMs) of genome evolution. These models explain the origin of 
      the characteristic Pareto distribution of paralogous gene family sizes in 
      genomes, and model parameters that provide for the evolution of these 
      distributions within a realistic time frame have been identified. However, 
      extracting the temporal dynamics of genome evolution from discrete-space BDIM was 
      not technically feasible. We were interested in obtaining dynamic portraits of 
      the genome evolution process by developing a diffusion approximation of BDIM. 
      RESULTS: The diffusion version of BDIM belongs to a class of continuous-state 
      models whose dynamics is described by the Fokker-Plank equation and the 
      stationary solution could be any specified Pareto function. The diffusion models 
      have time-dependent solutions of a special kind, namely, generalized self-similar 
      solutions, which describe the transition from one stationary distribution of the 
      system to another; this provides for the possibility of examining the temporal 
      dynamics of genome evolution. Analysis of the generalized self-similar solutions 
      of the diffusion BDIM reveals a biphasic curve of genome growth in which the 
      initial, relatively short, self-accelerating phase is followed by a prolonged 
      phase of slow deceleration. This evolutionary dynamics was observed both when 
      genome growth started from zero and proceeded via innovation (a potential model 
      of primordial evolution), and when evolution proceeded from one stationary state 
      to another. In biological terms, this regime of evolution can be tentatively 
      interpreted as a punctuated-equilibrium-like phenomenon whereby evolutionary 
      transitions are accompanied by rapid gene amplification and innovation, followed 
      by slow relaxation to a new stationary state.
FAU - Karev, Georgy P
AU  - Karev GP
AD  - National Center for Biotechnology Information, National Library of Medicine, 
      National Institutes of Health Bethesda, MD 20894, USA.
FAU - Berezovskaya, Faina S
AU  - Berezovskaya FS
FAU - Koonin, Eugene V
AU  - Koonin EV
LA  - eng
PT  - Journal Article
PL  - England
TA  - Bioinformatics
JT  - Bioinformatics (Oxford, England)
JID - 9808944
SB  - IM
MH  - *Algorithms
MH  - *Biological Evolution
MH  - Chromosome Mapping/*methods
MH  - Computer Simulation
MH  - DNA Mutational Analysis/*methods
MH  - *Evolution, Molecular
MH  - Genetic Variation/genetics
MH  - *Models, Genetic
MH  - Sequence Analysis, DNA/*methods
EDAT- 2005/11/25 09:00
MHDA- 2007/09/06 09:00
CRDT- 2005/11/25 09:00
PHST- 2005/11/25 09:00 [pubmed]
PHST- 2007/09/06 09:00 [medline]
PHST- 2005/11/25 09:00 [entrez]
AID - 21/Suppl_3/iii12 [pii]
AID - 10.1093/bioinformatics/bti1202 [doi]
PST - ppublish
SO  - Bioinformatics. 2005 Nov 1;21 Suppl 3:iii12-9. doi: 
      10.1093/bioinformatics/bti1202.