dorsal/arxiv
View SchemaSimple stochastic birth and death models of genome evolution: Was there enough time for us to evolve?
| Authors | Georgy P. Karev, Yuri I. Wolf, Eugene V. Koonin |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0507020 |
| URL | https://arxiv.org/abs/q-bio/0507020 |
| Journal | Bioinformatics 2003, 19(15):1889-1900 |
Abstract
We show that simple stochastic models of genome evolution lead to power law asymptotics of protein domain family size distribution. These models, called Birth, Death and Innovation Models (BDIM), represent a special class of balanced birth-and-death processes, in which domain duplication and deletion rates are asymptotically equal up to the second order. The simplest, linear BDIM shows an excellent fit to the observed distributions of domain family size in diverse prokaryotic and eukaryotic genomes. However, the stochastic version of the linear BDIM explored here predicts that the actual size of large paralogous families is reached on an unrealistically long timescale. We show that introduction of non-linearity, which might be interpreted as interaction of a particular order between individual family members, allows the model to achieve genome evolution rates that are much better compatible with the current estimates of the rates of individual duplication/loss events.
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"abstract": "We show that simple stochastic models of genome evolution lead to power law\nasymptotics of protein domain family size distribution. These models, called\nBirth, Death and Innovation Models (BDIM), represent a special class of\nbalanced birth-and-death processes, in which domain duplication and deletion\nrates are asymptotically equal up to the second order. The simplest, linear\nBDIM shows an excellent fit to the observed distributions of domain family size\nin diverse prokaryotic and eukaryotic genomes. However, the stochastic version\nof the linear BDIM explored here predicts that the actual size of large\nparalogous families is reached on an unrealistically long timescale. We show\nthat introduction of non-linearity, which might be interpreted as interaction\nof a particular order between individual family members, allows the model to\nachieve genome evolution rates that are much better compatible with the current\nestimates of the rates of individual duplication/loss events.",
"arxiv_id": "q-bio/0507020",
"authors": [
"Georgy P. Karev",
"Yuri I. Wolf",
"Eugene V. Koonin"
],
"categories": [
"q-bio.GN",
"q-bio.PE"
],
"journal_ref": "Bioinformatics 2003, 19(15):1889-1900",
"title": "Simple stochastic birth and death models of genome evolution: Was there enough time for us to evolve?",
"url": "https://arxiv.org/abs/q-bio/0507020"
},
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