6,861 research outputs found
An algorithmic view of gene teams
International audienc
Troping the Enemy: Metaphor, Culture, and the Big Data Black Boxes of National Security
This article considers how cultural understanding is being brought into the work of the Intelligence Advanced Research Projects Activity (IARPA), through an analysis of its Metaphor program. It examines the type of social science underwriting this program, unpacks implications of the agency’s conception of metaphor for understanding so-called cultures of interest, and compares IARPA’s to competing accounts of how metaphor works to create cultural meaning. The article highlights some risks posed by key deficits in the Intelligence Community\u27s (IC) approach to culture, which relies on the cognitive linguistic theories of George Lakoff and colleagues. It also explores the problem of the opacity of these risks for analysts, even as such predictive cultural analytics are becoming a part of intelligence forecasting. This article examines the problem of information secrecy in two ways, by unpacking the opacity of “black box,” algorithm-based social science of culture for end users with little appreciation of their potential biases, and by evaluating the IC\u27s nontransparent approach to foreign cultures, as it underwrites national security assessments
Easy identification of generalized common and conserved nested intervals
In this paper we explain how to easily compute gene clusters, formalized by
classical or generalized nested common or conserved intervals, between a set of
K genomes represented as K permutations. A b-nested common (resp. conserved)
interval I of size |I| is either an interval of size 1 or a common (resp.
conserved) interval that contains another b-nested common (resp. conserved)
interval of size at least |I|-b. When b=1, this corresponds to the classical
notion of nested interval. We exhibit two simple algorithms to output all
b-nested common or conserved intervals between K permutations in O(Kn+nocc)
time, where nocc is the total number of such intervals. We also explain how to
count all b-nested intervals in O(Kn) time. New properties of the family of
conserved intervals are proposed to do so
Status and Future Perspectives for Lattice Gauge Theory Calculations to the Exascale and Beyond
In this and a set of companion whitepapers, the USQCD Collaboration lays out
a program of science and computing for lattice gauge theory. These whitepapers
describe how calculation using lattice QCD (and other gauge theories) can aid
the interpretation of ongoing and upcoming experiments in particle and nuclear
physics, as well as inspire new ones.Comment: 44 pages. 1 of USQCD whitepapers
Research and Education in Computational Science and Engineering
Over the past two decades the field of computational science and engineering
(CSE) has penetrated both basic and applied research in academia, industry, and
laboratories to advance discovery, optimize systems, support decision-makers,
and educate the scientific and engineering workforce. Informed by centuries of
theory and experiment, CSE performs computational experiments to answer
questions that neither theory nor experiment alone is equipped to answer. CSE
provides scientists and engineers of all persuasions with algorithmic
inventions and software systems that transcend disciplines and scales. Carried
on a wave of digital technology, CSE brings the power of parallelism to bear on
troves of data. Mathematics-based advanced computing has become a prevalent
means of discovery and innovation in essentially all areas of science,
engineering, technology, and society; and the CSE community is at the core of
this transformation. However, a combination of disruptive
developments---including the architectural complexity of extreme-scale
computing, the data revolution that engulfs the planet, and the specialization
required to follow the applications to new frontiers---is redefining the scope
and reach of the CSE endeavor. This report describes the rapid expansion of CSE
and the challenges to sustaining its bold advances. The report also presents
strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie
Bidirectional best hit r-window gene clusters
<p>Abstract</p> <p>Background</p> <p><it>Conserved gene clusters </it>are groups of genes that are located close to one another in the genomes of several species. They tend to code for proteins that have a functional interaction. The identification of conserved gene clusters is an important step towards understanding genome evolution and predicting gene function.</p> <p>Results</p> <p>In this paper, we propose a novel pairwise gene cluster model that combines the notion of bidirectional best hits with the <it>r</it>-window model introduced in 2003 by Durand and Sankoff. The bidirectional best hit (BBH) constraint removes the need to specify the minimum number of shared genes in the <it>r</it>-window model and improves the relevance of the results. We design a subquadratic time algorithm to compute the set of BBH <it>r</it>-window gene clusters efficiently.</p> <p>Conclusion</p> <p>We apply our cluster model to the comparative analysis of <it>E. coli </it>K-12 and <it>B. subtilis </it>and perform an extensive comparison between our new model and the gene teams model developed by Bergeron <it>et al</it>. As compared to the gene teams model, our new cluster model has a slightly lower recall but a higher precision at all levels of recall when the results were ranked using statistical tests. An analysis of the most significant BBH <it>r</it>-window gene cluster show that they correspond to known operons.</p
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