111 research outputs found
Recommended from our members
A genetic dominance simulation program and its distribution web site for estimates of population genetic statistics
In order to aid comparison of estimates of genetic parameters between dominant and codominant makers for population genetics society, we developed a genetic dominance simulation program to determine how the dominance and biallelism could affect the estimation of population genetic statistics. The simulation indicates that genetic diversities within populations based on allozyme allele frequencies that were transformed into biallelic dominant data were significantly lower than for nontransformed multiallelic codominant data, while population differentiation was biased upwardly in each experimental species. Microsoft Active Server Pages (ASP) is combined with Active Data Objects (ADO) to create a dynamic web site for the distribution of the simulation program. The user's information is required to be registered into a database and they can also register their published papers to be shared with genetics community.Keywords: Genetic dominance simulation, Active Server Pages, Active Data Object
Recommended from our members
Nuclear and mitochondrial DNA polymorphism and phylogeny in the California closed-cone pines
We studied genetic polymorphism and phylogeny using nuclear random amplified polymorphic DNA markers (RAPDs) and mitochondrial DNA (mtDNA) restriction fragment length polymorphisms (RFLPs) in the three California Closed-Cone Pines: Pinus attenuata Lemm., P. muricata D. Don, and P. radiata D. Don. A total of 343 to 384 trees derived from 13 populations were analyzed using 13 mitochondria' gene probes and two restriction enzymes, and more than 90 RAPD loci generated by 22 primers. Southern hybridization was used to test homology among comigrating RAPD markers. Segregation analysis and Southern hybridization were carried out to distinguish between RAPD fragments of nuclear and organellar origin. Estimates of genetic diversity and population differentiation, and phylogenetic analyses based on RAPD and RFLP markers, were compared with those based on allozymes from a similar study. Twenty-eight distinct mtDNA haplotypes were detected among the three species. All three species showed limited variability within populations, but strong differentiation among populations. Based on haplotype frequencies, genetic diversity within populations (Hs) averaged 0.22, and population differentiation (GsT and 0) exceeded 0.78. Analysis of molecular variance (AMOVA) also revealed that more than 90% of the variation resided among populations. Species and populations could be readily distinguished by unique haplotypes, often using the combination of only a few probes. Twenty-eight of 30 (93%) comigrating RAPD fragments tested were homologous by Southern hybridization. Hybridization with enriched mtDNA, and chloroplast DNA (cpDNA) clones, identified one fragment as being of mtDNA origin and two as being of cpDNA origin, among 142 RAPD fragments surveyed. RAPD markers revealed moderately higher intrapopulation gene diversity and significantly higher total genetic diversity and population differentiation than did allozyme markers for each species. Simulation analysis to study effects of dominance on RAPD diversity suggested that dominance substantially depressed values of diversity within populations and inflated values of differentiation among populations. By comparison to our empirical analyses, we inferred that the underlying diversity of RAPD markers is substantially greater than that of allozymes. Results of phylogenetic analysis of RAPD markers were largely consistent with those from allozyme analysis, though they had many minor differences. Joint phylogenetic analysis of both the RAPD and allozyme markers strongly supported a common ancestor for P. radiata and P. attenuata, and south to north migration histories for all three species. Dendrograms based on mtDNA analysis, however, strongly disagreed with those based on allozymes, RAPDs, chloroplast DNA and morphological traits, suggesting convergent genome evolution
On the complexity of undominated core and farsighted solution concepts in coalition games
ABSTRACT In this paper, we study the computational complexity of solution concepts in the context of coalitional games. Firstly, we distinguish two different kinds of core, the undominated core and excess core, and investigate the difference and relationship between them. Secondly, we thoroughly investigate the computational complexity of undominated core and three farsighted solution concepts-farsighted core, farsighted stable set and largest consistent set
A Machine Learning Framework for Resource Allocation Assisted by Cloud Computing
Conventionally, the resource allocation is formulated as an optimization problem and solved online with
instantaneous scenario information. Since most resource allocation problems are not convex, the optimal solutions
are very difficult to be obtained in real time. Lagrangian relaxation or greedy methods are then often employed,
which results in performance loss. Therefore, the conventional methods of resource allocation are facing great
challenges to meet the ever-increasing QoS requirements of users with scarce radio resource. Assisted by cloud
computing, a huge amount of historical data on scenarios can be collected for extracting similarities among scenarios
using machine learning. Moreover, optimal or near-optimal solutions of historical scenarios can be searched offline
and stored in advance. When the measured data of current scenario arrives, the current scenario is compared with
historical scenarios to find the most similar one. Then, the optimal or near-optimal solution in the most similar
historical scenario is adopted to allocate the radio resources for the current scenario. To facilitate the application
of new design philosophy, a machine learning framework is proposed for resource allocation assisted by cloud
computing. An example of beam allocation in multi-user massive multiple-input-multiple-output (MIMO) systems
shows that the proposed machine-learning based resource allocation outperforms conventional methods
- …