World Wide Diversity of \u3ci\u3ePhytophthora capsici\u3c/i\u3e

The plant pathogen Phytophthora capsici is a genetically diverse organism that is a global problem. It effects many crops across the Solanacea, Cucurbitacea, andLeguminosea. As a result of the large diversity between individuals (and by extension populations) it has been previously near impossible to make meaningful comparisons between individuals of geographically distinct locations. Here we present the results of applying Next Generation Sequencing (NGS) technologies to a representative panel of isolates. This information and data is further used to demonstrate how this diversity has a functionally relevent effect on a class of proteins responsible for the infectious process. We also demonstrate the application of these technologies and techniques to even lesser studied plant pathogen systems and how they can be used to make intelligent decisions about isolate selection for future studies

Development of tools for the automated analysis of spectra generated by tandem mass spectrometry

Background While multiple tools exist for the analysis and identification of spectra generated in shotgun proteomics experiments, few easily implemented tools exist that allow for the automated analysis of the quality of spectra. A researcher’s knowledge of the quality of a spectra from an experiment can be helpful in determining possible reasons for misidentification or lack of identification of spectra in a sample. Materials and methods We are developing a automated high throughput method that analyses spectra from 2d-LC-MS/MS datasets to determine their quality and overall determines the quality of the run. We will then compare our programs to existing programs that perform a similar function. Our program calculates a quality score based on the following metrics: signal/noise ratio, absolute signal intensity, peak number, predicted mass distances between peak, and percent of incoming mass accounted for by peaks. These scores are then graphed against the outputs of common database search algorithms in order to display the following four categories: High-quality/Identified, High-quality/Unidentified, Low-quality/Identified, and Low-quality/Unidentified. We are currently testing the algorithm against 2d-LC-MS/MS runs of a mixed protein standard and blanks with no peptide spectra. The application samples are a time series of metaproteomes collected from environmental ground waters after biostimulation

Development of tools for the automated analysis of spectra generated by tandem mass spectrometry

Background While multiple tools exist for the analysis and identification of spectra generated in shotgun proteomics experiments, few easily implemented tools exist that allow for the automated analysis of the quality of spectra. A researcher’s knowledge of the quality of a spectra from an experiment can be helpful in determining possible reasons for misidentification or lack of identification of spectra in a sample. Materials and methods We are developing a automated high throughput method that analyses spectra from 2d-LC-MS/MS datasets to determine their quality and overall determines the quality of the run. We will then compare our programs to existing programs that perform a similar function. Our program calculates a quality score based on the following metrics: signal/noise ratio, absolute signal intensity, peak number, predicted mass distances between peak, and percent of incoming mass accounted for by peaks. These scores are then graphed against the outputs of common database search algorithms in order to display the following four categories: High-quality/Identified, High-quality/Unidentified, Low-quality/Identified, and Low-quality/Unidentified. We are currently testing the algorithm against 2d-LC-MS/MS runs of a mixed protein standard and blanks with no peptide spectra. The application samples are a time series of metaproteomes collected from environmental ground waters after biostimulation

100K Pathogen Genome Project: 306 Listeria Draft Genome Sequences for Food Safety and Public Health.

Listeria monocytogenes is a food-associated bacterium that is responsible for food-related illnesses worldwide. This is the initial public release of 306 L. monocytogenes genome sequences as part of the 100K Pathogen Genome Project. These isolates represent global genomic diversity in L. monocytogenes

Draft Genome Sequences of 1,183 Salmonella Strains from the 100K Pathogen Genome Project.

Salmonella is a common food-associated bacterium that has substantial impact on worldwide human health and the global economy. This is the public release of 1,183 Salmonella draft genome sequences as part of the 100K Pathogen Genome Project. These isolates represent global genomic diversity in the Salmonella genus

Large-Scale Release of Campylobacter Draft Genomes: Resources for Food Safety and Public Health from the 100K Pathogen Genome Project.

Campylobacter is a food-associated bacterium and a leading cause of foodborne illness worldwide, being associated with poultry in the food supply. This is the initial public release of 202 Campylobacter genome sequences as part of the 100K Pathogen Genome Project. These isolates represent global genomic diversity in the Campylobacter genus

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe

Combined searches for the production of supersymmetric top quark partners in proton-proton collisions at root s=13 TeV

A combination of searches for top squark pair production using proton-proton collision data at a center-of-mass energy of 13 TeV at the CERN LHC, corresponding to an integrated luminosity of 137 fb(-1) collected by the CMS experiment, is presented. Signatures with at least 2 jets and large missing transverse momentum are categorized into events with 0, 1, or 2 leptons. New results for regions of parameter space where the kinematical properties of top squark pair production and top quark pair production are very similar are presented. Depending on themodel, the combined result excludes a top squarkmass up to 1325 GeV for amassless neutralino, and a neutralinomass up to 700 GeV for a top squarkmass of 1150 GeV. Top squarks with masses from 145 to 295 GeV, for neutralino masses from 0 to 100 GeV, with a mass difference between the top squark and the neutralino in a window of 30 GeV around the mass of the top quark, are excluded for the first time with CMS data. The results of theses searches are also interpreted in an alternative signal model of dark matter production via a spin-0 mediator in association with a top quark pair. Upper limits are set on the cross section for mediator particle masses of up to 420 GeV

Probing effective field theory operators in the associated production of top quarks with a Z boson in multilepton final states at root s=13 TeV

Peer reviewe