45,780 research outputs found
A MOSAIC of methods: Improving ortholog detection through integration of algorithmic diversity
Ortholog detection (OD) is a critical step for comparative genomic analysis
of protein-coding sequences. In this paper, we begin with a comprehensive
comparison of four popular, methodologically diverse OD methods: MultiParanoid,
Blat, Multiz, and OMA. In head-to-head comparisons, these methods are shown to
significantly outperform one another 12-30% of the time. This high
complementarity motivates the presentation of the first tool for integrating
methodologically diverse OD methods. We term this program MOSAIC, or Multiple
Orthologous Sequence Analysis and Integration by Cluster optimization. Relative
to component and competing methods, we demonstrate that MOSAIC more than
quintuples the number of alignments for which all species are present, while
simultaneously maintaining or improving functional-, phylogenetic-, and
sequence identity-based measures of ortholog quality. Further, we demonstrate
that this improvement in alignment quality yields 40-280% more confidently
aligned sites. Combined, these factors translate to higher estimated levels of
overall conservation, while at the same time allowing for the detection of up
to 180% more positively selected sites. MOSAIC is available as python package.
MOSAIC alignments, source code, and full documentation are available at
http://pythonhosted.org/bio-MOSAIC
Using stock returns to identify government spending shocks
This paper explores a new approach to identifying government spending shocks which avoids many of the shortcomings of existing approaches. The new approach is to identify government spending shocks with statistical innovations to the accumulated excess returns of large US military contractors. This strategy is used to estimate the dynamic responses of output, hours, consumption and real wages to a government spending shock. We find that positive government spending shocks are associated with increases in output, hours, and consumption. Real wages initially decline after a government spending shock and then rise after a year. We estimate the government spending multiplier associated with increases in military spending to be about 0.6 over a horizon of 5 years.Fiscal policy ; Government spending policy ; Stocks
High energy flare physics group summary
The contributions of the High Energy Flare Physics Special Session in the American Astronomical Society Solar Physics Division Meeting are reviewed. Oral and poster papers were presented on observatories and instruments available for the upcoming solar maximum. Among these are the space-based Gamma Ray Observatory, the Solar Flare and Cosmic Burst Gamma Ray Experiment on the Ulysses spacecraft, the Soft X Ray Telescope on the spacecraft Solar-A, and the balloon-based Gamma Ray Imaging Device. Ground based observatories with new capabilities include the BIMA mm-wave interferometer (Univ. of California, Berkeley; Univ. of Illinois; Univ. of Maryland), Owens Valley Radio Observatory and the Very Large Array. The highlights of the various instrument performances are reported and potential data correlations and collaborations are suggested
An investigation into the relationship between long-term Posttraumatic Stress Disorder symptoms and coping in Australian volunteer firefighters
Design of two-dimensional particle assemblies using isotropic pair interactions with an attractive well
Using ground-state and relative-entropy based inverse design strategies,
isotropic interactions with an attractive well are determined to stabilize and
promote as- sembly of particles into two-dimensional square, honeycomb, and
kagome lattices. The design rules inferred from these results are discussed and
validated in the dis- covery of interactions that favor assembly of the highly
open truncated-square and truncated-hexagonal lattices.Comment: 11 pages, 5 figures and supplemental materia
Mixtures of Common Skew-t Factor Analyzers
A mixture of common skew-t factor analyzers model is introduced for
model-based clustering of high-dimensional data. By assuming common component
factor loadings, this model allows clustering to be performed in the presence
of a large number of mixture components or when the number of dimensions is too
large to be well-modelled by the mixtures of factor analyzers model or a
variant thereof. Furthermore, assuming that the component densities follow a
skew-t distribution allows robust clustering of skewed data. The alternating
expectation-conditional maximization algorithm is employed for parameter
estimation. We demonstrate excellent clustering performance when our model is
applied to real and simulated data.This paper marks the first time that skewed
common factors have been used
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