2,333 research outputs found
Information Geometry and Evolutionary Game Theory
The Shahshahani geometry of evolutionary game theory is realized as the
information geometry of the simplex, deriving from the Fisher information
metric of the manifold of categorical probability distributions. Some essential
concepts in evolutionary game theory are realized information-theoretically.
Results are extended to the Lotka-Volterra equation and to multiple population
systems.Comment: Added reference
The Art of War: Beyond Memory-one Strategies in Population Games
We define a new strategy for population games based on techniques from
machine learning and statistical inference that is essentially uninvadable and
can successfully invade (significantly more likely than a neutral mutant)
essentially all known memory-one strategies for the prisoner's dilemma and
other population games, including ALLC (always cooperate), ALLD (always
defect), tit-for-tat (TFT), win-stay-lose-shift (WSLS), and zero determinant
(ZD) strategies, including extortionate and generous strategies. We will refer
to a player using this strategy as an "information player" and the specific
implementation as . Such players use the history of play to identify
opponent's strategies and respond accordingly, and naturally learn to cooperate
with each other.Comment: 16 pages, 4 figure
Comprehensive Detection of Genes Causing a Phenotype using Phenotype Sequencing and Pathway Analysis
Discovering all the genetic causes of a phenotype is an important goal in
functional genomics. In this paper we combine an experimental design for
multiple independent detections of the genetic causes of a phenotype, with a
high-throughput sequencing analysis that maximizes sensitivity for
comprehensively identifying them. Testing this approach on a set of 24 mutant
strains generated for a metabolic phenotype with many known genetic causes, we
show that this pathway-based phenotype sequencing analysis greatly improves
sensitivity of detection compared with previous methods, and reveals a wide
range of pathways that can cause this phenotype. We demonstrate our approach on
a metabolic re-engineering phenotype, the PEP/OAA metabolic node in E. coli,
which is crucial to a substantial number of metabolic pathways and under
renewed interest for biofuel research. Out of 2157 mutations in these strains,
pathway-phenoseq discriminated just five gene groups (12 genes) as
statistically significant causes of the phenotype. Experimentally, these five
gene groups, and the next two high-scoring pathway-phenoseq groups, either have
a clear connection to the PEP metabolite level or offer an alternative path of
producing oxaloacetate (OAA), and thus clearly explain the phenotype. These
high-scoring gene groups also show strong evidence of positive selection
pressure, compared with strictly neutral selection in the rest of the genome
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