Genetic Sequence Matching Using D4M Big Data Approaches

Recent technological advances in Next Generation Sequencing tools have led to increasing speeds of DNA sample collection, preparation, and sequencing. One instrument can produce over 600 Gb of genetic sequence data in a single run. This creates new opportunities to efficiently handle the increasing workload. We propose a new method of fast genetic sequence analysis using the Dynamic Distributed Dimensional Data Model (D4M) - an associative array environment for MATLAB developed at MIT Lincoln Laboratory. Based on mathematical and statistical properties, the method leverages big data techniques and the implementation of an Apache Acculumo database to accelerate computations one-hundred fold over other methods. Comparisons of the D4M method with the current gold-standard for sequence analysis, BLAST, show the two are comparable in the alignments they find. This paper will present an overview of the D4M genetic sequence algorithm and statistical comparisons with BLAST.Comment: 6 pages; to appear in IEEE High Performance Extreme Computing (HPEC) 201

Rapid Sequence Identification of Potential Pathogens Using Techniques from Sparse Linear Algebra

The decreasing costs and increasing speed and accuracy of DNA sample collection, preparation, and sequencing has rapidly produced an enormous volume of genetic data. However, fast and accurate analysis of the samples remains a bottleneck. Here we present D$^{4}$RAGenS, a genetic sequence identification algorithm that exhibits the Big Data handling and computational power of the Dynamic Distributed Dimensional Data Model (D4M). The method leverages linear algebra and statistical properties to increase computational performance while retaining accuracy by subsampling the data. Two run modes, Fast and Wise, yield speed and precision tradeoffs, with applications in biodefense and medical diagnostics. The D$^{4}$RAGenS analysis algorithm is tested over several datasets, including three utilized for the Defense Threat Reduction Agency (DTRA) metagenomic algorithm contest

Probing the Nature of the Vela X Cocoon

Vela X is a pulsar wind nebula (PWN) associated with the active pulsar B0833-45 and contained within the Vela supernova remnant (SNR). A collimated X-ray filament ("cocoon") extends south-southwest from the pulsar to the center of Vela X. VLA observations uncovered radio emission coincident with the eastern edge of the cocoon and H.E.S.S. has detected TeV $\gamma$-ray emission from this region as well. Using XMM-\textit{Newton} archival data, covering the southern portion of this feature, we analyze the X-ray properties of the cocoon. The X-ray data are best fit by an absorbed nonequilibrium plasma model with a powerlaw component. Our analysis of the thermal emission shows enhanced abundances of O, Ne, and Mg within the cocoon, indicating the presence of ejecta-rich material from the propagation of the SNR reverse shock, consistent with Vela X being a disrupted PWN. We investigate the physical processes that excite the electrons in the PWN to emit in the radio, X-ray and $\gamma$-ray bands. The radio and non-thermal X-ray emission can be explained by synchrotron emission. We model the $\gamma$-ray emission by Inverse Compton scattering of electrons off of cosmic microwave background (CMB) photons. We use a 3-component broken power law to model the synchrotron emission, finding an intrinsic break in the electron spectrum at $\sim5 \times 10^{6}$ keV and a cooling break at $\sim$ 5.5 $\times 10^{10}$ keV. This cooling break along with a magnetic field strength of 5 $\times 10^{-6}$ G indicate that the synchrotron break occurs at $\sim$1 keV.Comment: accepted for publication to ApJ

“Hearing from All Sides” How Legislative Testimony Influences State Level Policy-Makers in the United States

Background: This paper investigates whether state legislators find testimony influential, to what extent testimony influences policy-makers’ decisions, and defines the features of testimony important in affecting policy-makers’ decisions. Methods: We used a mixed method approach to analyze responses from 862 state-level legislators in the United States (U.S.). Data were collected via a phone survey from January-October, 2012. Qualitative data were analyzed using a general inductive approach and codes were designed to capture the most prevalent themes. Descriptive statistics and cross tabulations were also completed on thematic and demographic data to identify additional themes. Results: Most legislators, regardless of political party and other common demographics, find testimony influential, albeit with various definitions of influence. While legislators reported that testimony influenced their awareness or encouraged them to take action like conducting additional research, only 6% reported that testimony changes their vote. Among those legislators who found testimony influential, characteristics of the presenter (e.g., credibility, knowledge of the subject) were the most important aspects of testimony. Legislators also noted several characteristics of testimony content as important, including use of credible, unbiased information and data. Conclusion: Findings from this study can be used by health advocates, researchers, and individuals to fine tune the delivery of materials and messages to influence policy-makers during legislative testimony. Increasing the likelihood that information from scholars will be used by policy-makers may lead to the adoption of more health policies that are informed by scientific and practice-based evidence

Toward optimal implementation of cancer prevention and control programs in public health: A study protocol on mis-implementation

Abstract Background Much of the cancer burden in the USA is preventable, through application of existing knowledge. State-level funders and public health practitioners are in ideal positions to affect programs and policies related to cancer control. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Greater attention to mis-implementation should lead to use of effective interventions and more efficient expenditure of resources, which in the long term, will lead to more positive cancer outcomes. Methods This is a three-phase study that takes a comprehensive approach, leading to the elucidation of tactics for addressing mis-implementation. Phase 1: We assess the extent to which mis-implementation is occurring among state cancer control programs in public health. This initial phase will involve a survey of 800 practitioners representing all states. The programs represented will span the full continuum of cancer control, from primary prevention to survivorship. Phase 2: Using data from phase 1 to identify organizations in which mis-implementation is particularly high or low, the team will conduct eight comparative case studies to get a richer understanding of mis-implementation and to understand contextual differences. These case studies will highlight lessons learned about mis-implementation and identify hypothesized drivers. Phase 3: Agent-based modeling will be used to identify dynamic interactions between individual capacity, organizational capacity, use of evidence, funding, and external factors driving mis-implementation. The team will then translate and disseminate findings from phases 1 to 3 to practitioners and practice-related stakeholders to support the reduction of mis-implementation. Discussion This study is innovative and significant because it will (1) be the first to refine and further develop reliable and valid measures of mis-implementation of public health programs; (2) bring together a strong, transdisciplinary team with significant expertise in practice-based research; (3) use agent-based modeling to address cancer control implementation; and (4) use a participatory, evidence-based, stakeholder-driven approach that will identify key leverage points for addressing mis-implementation among state public health programs. This research is expected to provide replicable computational simulation models that can identify leverage points and public health system dynamics to reduce mis-implementation in cancer control and may be of interest to other health areas

A target-based high throughput screen yields Trypanosoma brucei hexokinase small molecule inhibitors with antiparasitic activity. PLoS Negl Trop. Dis

Abstract Background: The parasitic protozoan Trypanosoma brucei utilizes glycolysis exclusively for ATP production during infection of the mammalian host. The first step in this metabolic pathway is mediated by hexokinase (TbHK), an enzyme essential to the parasite that transfers the c-phospho of ATP to a hexose. Here we describe the identification and confirmation of novel small molecule inhibitors of bacterially expressed TbHK1, one of two TbHKs expressed by T. brucei, using a high throughput screening assay

Limits to reconstructing paleotopography from thermochronometer data

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95240/1/jgrf851.pd