343 research outputs found
On the Existence of Telescopers for P-recursive Sequences
We extend the criterion on the existence of telescopers for hypergeometric
terms to the case of P-recursive sequences. This criterion is based on the
concept of integral bases and the generalized Abramov-Petkovsek reduction for
P-recursive sequences.Comment: 18 page
Percolation on interacting networks with feedback-dependency links
When real networks are considered, coupled networks with connectivity and feedback-dependency links are not rare but more general. Here we develop a mathematical framework and study numerically and analytically percolation of interacting networks with feedback-dependency links. We find that when nodes of between networks are lowly connected, the system undergoes from second order transition through hybrid order transition to first order transition as coupling strength increases. And, as average degree of each inter-network increases, first order region becomes smaller and second-order region becomes larger but hybrid order region almost keep constant. Especially, the results implies that average degree \bar{k} between intra-networks has a little influence on robustness of system for weak coupling strength, but for strong coupling strength corresponding to first order transition system become robust as \bar{k} increases. However, when average degree k of inter-network is increased, the system become robust for all coupling strength. Additionally, when nodes of between networks are highly connected, the hybrid order region disappears and the system first order region becomes larger and secondorder region becomes smaller. Moreover, we find that the existence of feedback dependency links between interconnecting networks makes the system extremely vulnerable by comparing non-feedback condition for the same parameters.First author draf
Detection of selection signatures in dairy and beef cattle using high-density genomic information
peer-reviewedBackground
Artificial selection for economically important traits in cattle is expected to have left distinctive selection signatures on the genome. Access to high-density genotypes facilitates the accurate identification of genomic regions that have undergone positive selection. These findings help to better elucidate the mechanisms of selection and to identify candidate genes of interest to breeding programs.
Results
Information on 705 243 autosomal single nucleotide polymorphisms (SNPs) in 3122 dairy and beef male animals from seven cattle breeds (Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental) were used to detect selection signatures by applying two complementary methods, integrated haplotype score (iHS) and global fixation index (FST). To control for false positive results, we used false discovery rate (FDR) adjustment to calculate adjusted iHS within each breed and the genome-wide significance level was about 0.003. Using the iHS method, 83, 92, 91, 101, 85, 101 and 86 significant genomic regions were detected for Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental cattle, respectively. None of these regions was common to all seven breeds. Using the FST approach, 704 individual SNPs were detected across breeds. Annotation of the regions of the genome that showed selection signatures revealed several interesting candidate genes i.e. DGAT1, ABCG2, MSTN, CAPN3, FABP3, CHCHD7, PLAG1, JAZF1, PRKG2, ACTC1, TBC1D1, GHR, BMP2, TSG1, LYN, KIT and MC1R that play a role in milk production, reproduction, body size, muscle formation or coat color. Fifty-seven common candidate genes were found by both the iHS and global FST methods across the seven breeds. Moreover, many novel genomic regions and genes were detected within the regions that showed selection signatures; for some candidate genes, signatures of positive selection exist in the human genome. Multilevel bioinformatic analyses of the detected candidate genes suggested that the PPAR pathway may have been subjected to positive selection.
Conclusions
This study provides a high-resolution bovine genomic map of positive selection signatures that are either specific to one breed or common to a subset of the seven breeds analyzed. Our results will contribute to the detection of functional candidate genes that have undergone positive selection in future studies.This study was financially supported by a grant from the Irish Department of Agriculture, Food and Marine Research Stimulus Fund (11/S/112), the Agricultural Science and Technology Innovation Program (No. ASTIP-IAS-TS-6) and the Natural Science Foundation of China (No. 31200927)
Exact results of the limited penetrable horizontal visibility graph associated to random time series and its application
The limited penetrable horizontal visibility algorithm is a new time analysis
tool and is a further development of the horizontal visibility algorithm. We
present some exact results on the topological properties of the limited
penetrable horizontal visibility graph associated with random series. We show
that the random series maps on a limited penetrable horizontal visibility graph
with exponential degree distribution ,
independent of the probability distribution from which the series was
generated. We deduce the exact expressions of the mean degree and the
clustering coefficient and demonstrate the long distance visibility property.
Numerical simulations confirm the accuracy of our theoretical results. We then
examine several deterministic chaotic series (a logistic map, the
Hnon map, the Lorentz system, and an energy price chaotic system)
and a real crude oil price series to test our results. The empirical results
show that the limited penetrable horizontal visibility algorithm is direct, has
a low computational cost when discriminating chaos from uncorrelated
randomness, and is able to measure the global evolution characteristics of the
real time series.Comment: 23 pages, 12 figure
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