233 research outputs found
Statistical Phylogenetic Tree Analysis Using Differences of Means
We propose a statistical method to test whether two phylogenetic trees with
given alignments are significantly incongruent. Our method compares the two
distributions of phylogenetic trees given by the input alignments, instead of
comparing point estimations of trees. This statistical approach can be applied
to gene tree analysis for example, detecting unusual events in genome evolution
such as horizontal gene transfer and reshuffling. Our method uses difference of
means to compare two distributions of trees, after embedding trees in a vector
space. Bootstrapping alignment columns can then be applied to obtain p-values.
To compute distances between means, we employ a "kernel trick" which speeds up
distance calculations when trees are embedded in a high-dimensional feature
space, e.g. splits or quartets feature space. In this pilot study, first we
test our statistical method's ability to distinguish between sets of gene trees
generated under coalescence models with species trees of varying dissimilarity.
We follow our simulation results with applications to various data sets of
gophers and lice, grasses and their endophytes, and different fungal genes from
the same genome. A companion toolkit, {\tt Phylotree}, is provided to
facilitate computational experiments.Comment: 17 pages, 6 figure
Spatially-distributed coverage optimization and control with limited-range interactions
This paper presents coordination algorithms for groups of mobile agents
performing deployment and coverage tasks. As an important modeling constraint,
we assume that each mobile agent has a limited sensing/communication radius.
Based on the geometry of Voronoi partitions and proximity graphs, we analyze a
class of aggregate objective functions and propose coverage algorithms in
continuous and discrete time. These algorithms have convergence guarantees and
are spatially distributed with respect to appropriate proximity graphs.
Numerical simulations illustrate the results.Comment: 31 pages, some figures left out because of size limits. Complete
preprint version available at http://motion.csl.uiuc.ed
OPTIMAL SUPPLEMENTAL COVERAGE OPTION CROP INSURANCE DECISION FOR KENTUCKY COMMODITY CROP PRODUCERS
The 2018 Farm Bill has reopened commodity program enrollment for producers, and thus renewed interest in the Supplemental Coverage Option (SCO) of the Federal Crop Insurance Program (FCIP). This thesis examines the potential risk management benefits afforded to Kentucky corn, soybean and wheat producers by the SCO.
A simulation model is used to rank downside-risk minimization of the common Multi-peril Crop Insurance Policies (MPCI) policies both with and without the SCO for various farm-level yield risk and farm- to SCO area-level yield correlations.
The study found that the SCO endorsement was a component of every optimal insurance choice for all possible combinations examined in this study. Soybeans had the greatest homogeneity, while wheat had the greatest variability in optimal insurance choice.
The results show that the SCO should enter into a producer\u27s crop insurance decision and also commodity program enrollment decision — when applicable. The yearly commodity program enrollment deadlines occurring throughout the life of the current Farm Bill make this study especially timely
Approximating Mexican highways with slime mould
Plasmodium of Physarum polycephalum is a single cell visible by unaided eye.
During its foraging behavior the cell spans spatially distributed sources of
nutrients with a protoplasmic network. Geometrical structure of the
protoplasmic networks allows the plasmodium to optimize transport of nutrients
between remote parts of its body. Assuming major Mexican cities are sources of
nutrients how much structure of Physarum protoplasmic network correspond to
structure of Mexican Federal highway network? To find an answer undertook a
series of laboratory experiments with living Physarum polycephalum. We
represent geographical locations of major cities by oat flakes, place a piece
of plasmodium in Mexico city area, record the plasmodium's foraging behavior
and extract topology of nutrient transport networks. Results of our experiments
show that the protoplasmic network formed by Physarum is isomorphic, subject to
limitations imposed, to a network of principle highways. Ideas and results of
the paper may contribute towards future developments in bio-inspired road
planning
Co-evolution of density and topology in a simple model of city formation
We study the influence that population density and the road network have on
each others' growth and evolution. We use a simple model of formation and
evolution of city roads which reproduces the most important empirical features
of street networks in cities. Within this framework, we explicitely introduce
the topology of the road network and analyze how it evolves and interact with
the evolution of population density. We show that accessibility issues -pushing
individuals to get closer to high centrality nodes- lead to high density
regions and the appearance of densely populated centers. In particular, this
model reproduces the empirical fact that the density profile decreases
exponentially from a core district. In this simplified model, the size of the
core district depends on the relative importance of transportation and rent
costs.Comment: 13 pages, 13 figure
Non-Transgenic CRISPR-Mediated Knockout of Entire Ergot Alkaloid Gene Clusters in Slow-Growing Asexual Polyploid Fungi
The Epichloë species of fungi include seed-borne symbionts (endophytes) of cool-season grasses that enhance plant fitness, although some also produce alkaloids that are toxic to livestock. Selected or mutated toxin-free endophytes can be introduced into forage cultivars for improved livestock performance. Long-read genome sequencing revealed clusters of ergot alkaloid biosynthesis (EAS) genes in Epichloë coenophiala strain e19 from tall fescue (Lolium arundinaceum) and Epichloë hybrida Lp1 from perennial ryegrass (Lolium perenne). The two homeologous clusters in E. coenophiala—a triploid hybrid species—were 196 kb (EAS1) and 75 kb (EAS2), and the E. hybrida EAS cluster was 83 kb. As a CRISPR-based approach to target these clusters, the fungi were transformed with ribonucleoprotein (RNP) complexes of modified Cas9 nuclease (Cas9-2NLS) and pairs of single guide RNAs (sgRNAs), plus a transiently selected plasmid. In E. coenophiala, the procedure generated deletions of EAS1 and EAS2 separately, as well as both clusters simultaneously. The technique also gave deletions of the EAS cluster in E. hybrida and of individual alkaloid biosynthesis genes (dmaW and lolC) that had previously proved difficult to delete in E. coenophiala. Thus, this facile CRISPR RNP approach readily generates non-transgenic endophytes without toxin genes for use in research and forage cultivar improvement
Experimenting with database segmentation size vs time performance for mpiBLAST on an IBM HS21 blade cluster
Large-scale genomic projects such as the Epichloë festucae Genome Project require regular use of bioinformatic tools. When using BLAST in conjunction with larger databases, processing complex sequences often uses substantial computation time. Parallelization is considered a standard method of curbing extensive computing requirements and parallel implementations of BLAST, such as mpiBLAST, are freely available
MedSurv: a software application for creating, conducting and managing medical surveys and questionnaires
MedSurv is a system designed for the rapid creation and maintenance of research surveys and questionnaires that does not require programmer intervention. MedSurv is built with medical surveys in mind and utilizes a group-based permission control with additional security features to help ensure compliance with applicable healthcare regulations. MedSurv is designed as a module for DotNetNuke [1], an open source portal and content management system built with ASP.Net technology, and therefore can be deployed and managed as intranet, extranet, and web sites. At the same time, all data is stored at the researcher\u27s institution to guarantee the required data privacy. Thanks to its built-in support for user authentication and user roles, there is no need to create such functionality from scratch. However, a group-based permissions system is added to MedSurv to support sufficient granularity for access control. Although from the data access point of view data storage acts as a relational table, MedSurv uses a solution that we call virtual tables. The premise behind such a solution is that the structure of the tables is itself stored in a set of relational tables within the database, essentially creating a miniature database within the database. This additional layer is transparent to the user and removes the need for any programming or database knowledge. At the same time it gives the user the flexibility of changing the survey at runtime. Unlike a traditional structure that may require database developer\u27s involvement each time a survey is added or changed, with virtual tables there is very low developer and database administration need after launch. MedSurv allows for creating complex medical surveys and is, in particular, used to develop questionnaires for research driven data collection in the Department of Gastroenterology
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