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Search Results: 1 - 10 of 94823 matches for " Matthew W Peterson "
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TreeViewJ: An application for viewing and analyzing phylogenetic trees
Matthew W Peterson, Marc E Colosimo
Source Code for Biology and Medicine , 2007, DOI: 10.1186/1751-0473-2-7
Abstract: We present TreeViewJ, a Java tool for visualizing, editing and analyzing phylogenetic trees. The software allows researchers to color and change the width of branches that they wish to highlight, and add names to nodes. If collection dates are available for taxa, the software can map them onto a timeline, and sort the tree in ascending or descending date order.TreeViewJ is a tool for researchers to visualize, edit, "decorate," and produce publication-ready images of phylogenetic trees. It is open-source, and released under an GPL license, and available at http://treeviewj.sourceforge.net webcite.Phylogenetic trees are widely used to visualize evolutionary relationships between different organisms or samples of the same organism. There is a variety of both free and commercial tree visualization software [1-5] available, but limitations in these programs often require the user to use multiple programs for analysis, annotation, and display for publication. For some applications, such as epidemiological studies, the visualization of sample collection dates along with the tree would provide further insight into relationships. However, no currently available visualization packages provide this functionality.A variety of file formats exist for the storage of phylogenetic trees. Some, like the New Hampshire[6] format store only the node name and branch length information. Others, like the New Hampshire Extended [5] and Nexus[7] formats, can be used to store other data such as formatting and sequence data. Other file formats, such as the Lucid [8] and Structure of Descriptive Data (SDD) [9] formats have been used for the description of taxonomic data. Recently, a draft standard for an XML-based format, PhyloXML [10], has been released. XML-based formats are ideal for storing phylogenetic data because they can be easily interpreted by readily available general purpose software (thus eliminating the need for customized parsers), easily allow for annotation, and are extensible.
Nephele: genotyping via complete composition vectors and MapReduce
Marc E Colosimo, Matthew W Peterson, Scott Mardis, Lynette Hirschman
Source Code for Biology and Medicine , 2011, DOI: 10.1186/1751-0473-6-13
Abstract: Nephele is a suite of tools that uses the complete composition vector algorithm to represent each sequence in the dataset as a vector derived from its constituent k-mers by passing the need for multiple sequence alignment, and affinity propagation clustering to group the sequences into genotypes based on a distance measure over the vectors. Our methods produce results that correlate well with expert-defined clades or genotypes, at a fraction of the computational cost of traditional phylogenetic methods run on traditional hardware. Nephele can use the open-source Hadoop implementation of MapReduce to parallelize execution using multiple compute nodes. We were able to generate a neighbour-joined tree of over 10,000 16S samples in less than 2 hours.We conclude that using Nephele can substantially decrease the processing time required for generating genotype trees of tens to hundreds of organisms at genome scale sequence coverage.In the post-genomic era, as sequencing becomes ever cheaper and more routine, biological sequence analysis has provided many useful tools for the study and combat of infectious disease. These tools, which can include both experimental and computational methods, are important for molecular epidemiological studies [1-3], vaccine development [4-6], and microbial forensics [7-9]. One such method is genotyping, the grouping of samples based on their genetic sequence. This can be done experimentally [10-12] or computationally, either by identifying genetic signatures (nucleotide substrings which are only found in a single group of sequences) [13], or on the basis of genetic distance among the sequences [14-16]. These methods allow a researcher to split a group of sequences into distinct partitions for further analysis. In a forensics context, genotyping a sequence can yield clues on where the sequence comes from. In surveillance, genotyping can be used to examine the evolutionary footprint of a pathogen, for example, to identify areas where certain v
Effect of Sociality and Season on Gray Wolf (Canis lupus) Foraging Behavior: Implications for Estimating Summer Kill Rate
Matthew C. Metz,John A. Vucetich,Douglas W. Smith,Daniel R. Stahler,Rolf O. Peterson
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0017332
Abstract: Understanding how kill rates vary among seasons is required to understand predation by vertebrate species living in temperate climates. Unfortunately, kill rates are only rarely estimated during summer.
Correlation of sperm penetration assay score with polyspermy rate in in-vitro fertilization
Aoki Vincent W,Peterson C Matthew,Parker-Jones Kirtly,Hatasaka Harry H
Journal of Experimental and Clinical Assisted Reproduction (JECAR) , 2005, DOI: 10.1186/1743-1050-2-3
Abstract: Background The sperm penetration assay (SPA) is used to predict the fertilizing capacity of sperm. Thus, some programs rely on SPA scores to formulate insemination plans in conjunction with in-vitro fertilization (IVF) cycles. The purpose of this study was to evaluate if a relationship exists between SPA scores and polyspermy rates during conventional IVF cycles. Methods A total of 1350 consecutive IVF patients using conventional IVF insemination were evaluated in the study. Oocytes were inseminated three hours post-retrieval by the addition of 150,000 to 300,000 progressively motile sperm. Approximately 18 hours after insemination, the oocytes were evaluated for fertilization by the visualization of pronuclei. The presence of three or more pronuclei was indicative of polyspermy. Polyspermy rates, fertilization success, embryo quality, and pregnancy rates were analyzed retrospectively to evaluate their relationship with SPA score, count, motility, number of progressively motile sperm inseminated, oocyte pre-insemination incubation time, patient age, and diagnosis. Results A significant positive relationship was observed between SPA score and polyspermy rate (rs = 0.10, p < 0.05). Patients with a normal SPA score had significantly higher polyspermy rates than those with abnormal SPA scores (6.3% ± 1.5% vs. 2.0% ± 0.7%, p < 0.05). Fertilization percentage was significantly lower in the group with severely abnormal SPA scores versus all other SPA groups (57.5% ± 2.1% vs. 70.2% ± 1.3%, p < 0.005). Although embryo quality was not affected, both clinical pregnancy and implantation rates improved slightly as SPA score increased. In addition, there was a decrease in the rate of spontaneous abortion as SPA score increased. Conclusions These data indicate SPA score is positively correlated with polyspermy rates and IVF fertilization percentage. Additionally, there is a slight increase in clinical pregnancy rates, and embryo implantation rates with increased SPA. Furthermore, there is a slight decrease in spontaneous abortions rates related to increased SPA.
Evaluating Subdivisions for Identifying Extraneous Flow in Separate Sanitary Sewer Systems  [PDF]
Adam Lanning, Eric W. Peterson
Journal of Water Resource and Protection (JWARP) , 2012, DOI: 10.4236/jwarp.2012.46037
Abstract: Separate sanitary sewer systems are designed to convey sewage waste from municipal areas to a central treatment facility; they are not designed to handle water associated with precipitation events. However, intercept of groundwater (infiltration) and of flows through manholes or unauthorized connections (inflows) introduces rainwater into the sanitary sewer system. Infiltration/Inflow (I/I) increases the costs associated with treatment and can create additional environmental problems. Identifying and quantifying the volume I/I can be complicated and costly. A simple quantitative method was developed to quantify the extent of I/I occurring in sewer sheds. The method uses measured sewer flows, water usage, precipitation values, and land cover data to calculate the volume of extraneous flows. To assess its utility, the method was used to compare two urban sewer sheds, Holiday Knolls and Eagle View. Both sewer sheds showed evidence of I/I in excess of 200 gallons per day per inch-mile of sewer pipe (gpd/in-mile). Holiday Knolls, the older subdivision had an average I/I of 1912 gpd/in-mile, while Eagle View had an average of 1143 gpd/in-mile. The devel- oped method provided simple means to calculate I/I and to identify sewer sheds in need of repair.
Variation of Hyporheic Temperature Profiles in a Low Gradient Third-Order Agricultural Stream—A Statistical Approach  [PDF]
Vanessa Beach, Eric W. Peterson
Open Journal of Modern Hydrology (OJMH) , 2013, DOI: 10.4236/ojmh.2013.32008
Abstract: Sediment size governs advection, controlling the hydraulic conductivity of the stratum, and conduction, influencing the amount of surface area in contact between the sediment particles. To understand the role of sediment particle size on thermal profiles within the hyporheic zone, a statistical approach, involving general summary statistics and time series cross-correlation, was employed. Data were collected along two riffles: Site 1: gravel (d50 = 3.9 mm) and Site 2: sand (d50 =0.94 mm).Temperature probe grids collected 15-minute temperature data at 30, 60, 90, and140cm below the streambed surface over a 6 month period. Surface water and air temperature were recorded. Diel temperature signal penetration depth was limited to the upper 30cm of the streambed and was driven by advection. Surface seasonal trends were detected at greater depths, indicating that thermal pulses are transmitted initially by advection and by conduction to areas deeper in the hyporheic zone. Site 1 showed a high degree of thermal heterogeneity via a localized downwelling zone within a gaining stream environment. Site 2 exhibited a vertically and horizontally homogenized thermal environment attributed to an increased amount of sand sediments that limited advection and significant groundwater discharge that mediated the effects of downwelling surface water.
The Effects of Surface Water Velocity on Hyporheic Interchange  [PDF]
Timothy Sickbert, Eric W. Peterson
Journal of Water Resource and Protection (JWARP) , 2014, DOI: 10.4236/jwarp.2014.64035

When evaluating hyporheic exchange in a flowing stream, it is inappropriate to directly compare stream stage with subsurface hydraulic head (h) to determine direction and magnitude of the gradient between the stream and the subsurface. In the case of moving water, it is invalid to ignore velocity and to assume that stage equals the net downward pressure on the streambed.  The Bernoulli equation describes the distribution of energy within flowing fluids and implies that net pressure decreases as a function of velocity, i.e., the Venturi Effect, which sufficiently reduces the pressure on the streambed to create the appearance of a downward gradient when in fact the gradient may be upward with stream flow drawing water from the subsurface to the surface. A field study correlating the difference between subsurface head and stream stage in a low-gradient stream indicates that the effect is present and significant: shallow subsurface head increases less quickly than stage while deeper subsurface head increases more quickly. These results can substantially improve conceptual models and simulations of hyporheic flow.

VX Hydrolysis by Human Serum Paraoxonase 1: A Comparison of Experimental and Computational Results
Matthew W. Peterson, Steven Z. Fairchild, Tamara C. Otto, Mojdeh Mohtashemi, Douglas M. Cerasoli, Wenling E. Chang
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0020335
Abstract: Human Serum paraoxonase 1 (HuPON1) is an enzyme that has been shown to hydrolyze a variety of chemicals including the nerve agent VX. While wildtype HuPON1 does not exhibit sufficient activity against VX to be used as an in vivo countermeasure, it has been suggested that increasing HuPON1's organophosphorous hydrolase activity by one or two orders of magnitude would make the enzyme suitable for this purpose. The binding interaction between HuPON1 and VX has recently been modeled, but the mechanism for VX hydrolysis is still unknown. In this study, we created a transition state model for VX hydrolysis (VXts) in water using quantum mechanical/molecular mechanical simulations, and docked the transition state model to 22 experimentally characterized HuPON1 variants using AutoDock Vina. The HuPON1-VXts complexes were grouped by reaction mechanism using a novel clustering procedure. The average Vina interaction energies for different clusters were compared to the experimentally determined activities of HuPON1 variants to determine which computational procedures best predict how well HuPON1 variants will hydrolyze VX. The analysis showed that only conformations which have the attacking hydroxyl group of VXts coordinated by the sidechain oxygen of D269 have a significant correlation with experimental results. The results from this study can be used for further characterization of how HuPON1 hydrolyzes VX and design of HuPON1 variants with increased activity against VX.
Open-target sparse sensing of biological agents using DNA microarray
Mojdeh Mohtashemi, David K Walburger, Matthew W Peterson, Felicia N Sutton, Haley B Skaer, James C Diggans
BMC Bioinformatics , 2011, DOI: 10.1186/1471-2105-12-314
Abstract: A multivariate mathematical model based on the partial least squares regression (PLSR) was developed to detect the presence of three test organisms in mixed samples. When all 12,900 probes were used, the model correctly detected the signature of three test organisms in all mixed samples (mean(R2)) = 0.76, CI = 0.95), with a 6% false positive rate. A sampling algorithm was then developed to sparsely sample the probe space for a minimal number of probes required to capture the hybridization imprints of the test organisms. The PLSR detection model was capable of correctly identifying the presence of the three test organisms in all mixed samples using only 47 probes (mean(R2)) = 0.77, CI = 0.95) with nearly 100% specificity.We conceived an 'open-target' approach to biosensing, and hypothesized that a relatively small, non-specifically designed, DNA microarray is capable of identifying the presence of multiple organisms in mixed samples. Coupled with a mathematical model applied to laboratory generated data, and sparse sampling of capture probes, the prototype microarray platform was able to capture the signature of each organism in all mixed samples with high sensitivity and specificity. It was demonstrated that this new approach to biosensing closely follows the principles of sparse sensing.To date, most biosensors can be considered to be 'target-specific' systems in that their detection elements are built to respond to a fixed number of organisms, and are designed to be non-responsive in the absence of those organisms. In fielded sensors, PCR-based technologies are often selected for their specificity and low per-assay cost. While this targeted approach is very effective in an environment where specific biological events are expected, a biosensing infrastructure capable of rapidly responding to new or engineered biological threats while maintaining a low cost of operation requires increased flexibility. Targeted platforms, like those using specific PCR primers for qua
Bias of the Random Forest Out-of-Bag (OOB) Error for Certain Input Parameters  [PDF]
Matthew W. Mitchell
Open Journal of Statistics (OJS) , 2011, DOI: 10.4236/ojs.2011.13024
Abstract: Random Forest is an excellent classification tool, especially in the –omics sciences such as metabolomics, where the number of variables is much greater than the number of subjects, i.e., “n << p.” However, the choices for the arguments for the random forest implementation are very important. Simulation studies are performed to compare the effect of the input parameters on the predictive ability of the random forest. The number of variables sampled, m-try, has the largest impact on the true prediction error. It is often claimed that the out-of-bag error (OOB) is an unbiased estimate of the true prediction error. However, for the case where n << p, with the default arguments, the out-of-bag (OOB) error overestimates the true error, i.e., the random forest actually performs better than indicated by the OOB error. This bias is greatly reduced by subsampling without replacement and choosing the same number of observations from each group. However, even after these adjustments, there is a low amount of bias. The remaining bias occurs because when there are trees with equal predictive ability, the one that performs better on the in-bag samples will perform worse on the out-of-bag samples. Cross-validation can be performed to reduce the remaining bias.
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