design of selective peptide antibiotics by using the sequence moment concept

New antibiotics against multidrug-resistant bacteria are urgently needed, but rapid acquisition of resistance limits their usefulness. Endogenous antimicrobial peptides (AMPs) with moderate selectivity, but multimodal mechanism of action, have remained effective against bacteria for millions of years. Their therapeutic application, however, requires optimizing the balance between antibacterial activity and selectivity, so that rational design methods for increasing selectivity are highly desirable. We have created training (n=36) and testing (n=37) sets from frog-derived AMPs with determined therapeutic index (TI). The 'sequence moments' concept then enabled us to find a one-parameter linear model resulting in a good correlation between measured and predicted TI (r2=0.83 and 0.64 for each set, respectively). The concept was then used in the AMP-Designer algorithm to propose primary structures for highly selective AMPs against Gram-negative bacteria. Testing the activity of one such peptide produced a TI>200 as compared to the best AMP in the data-base, with TI=125

Efficient HTTP based I/O on very large datasets for high performance computing with the libdavix library

Remote data access for data analysis in high performance computing is commonly done with specialized data access protocols and storage systems. These protocols are highly optimized for high throughput on very large datasets, multi-streams, high availability, low latency and efficient parallel I/O. The purpose of this paper is to describe how we have adapted a generic protocol, the Hyper Text Transport Protocol (HTTP) to make it a competitive alternative for high performance I/O and data analysis applications in a global computing grid: the Worldwide LHC Computing Grid. In this work, we first analyze the design differences between the HTTP protocol and the most common high performance I/O protocols, pointing out the main performance weaknesses of HTTP. Then, we describe in detail how we solved these issues. Our solutions have been implemented in a toolkit called davix, available through several recent Linux distributions. Finally, we describe the results of our benchmarks where we compare the performance of davix against a HPC specific protocol for a data analysis use case.Comment: Presented at: Very large Data Bases (VLDB) 2014, Hangzho

GR@PPA 2.8: initial-state jet matching for weak boson production processes at hadron collisions

The initial-state jet matching method introduced in our previous studies has been applied to the event generation of single $W$ and $Z$ production processes and diboson ($W^{+}W^{-}$, $WZ$ and $ZZ$) production processes at hadron collisions in the framework of the GR@PPA event generator. The generated events reproduce the transverse momentum spectra of weak bosons continuously in the entire kinematical region. The matrix elements (ME) for hard interactions are still at the tree level. As in previous versions, the decays of weak bosons are included in the matrix elements. Therefore, spin correlations and phase-space effects in the decay of weak bosons are exact at the tree level. The program package includes custom-made parton shower programs as well as ME-based hard interaction generators in order to achieve self-consistent jet matching. The generated events can be passed to general-purpose event generators to make the simulation proceed down to the hadron level.Comment: 29 pages, 14 figures; minor changes to clarify the discussions, and corrections of typo

OPUCEM: A Library with Error Checking Mechanism for Computing Oblique Parameters

After a brief review of the electroweak radiative corrections to gauge-boson self-energies, otherwise known as the direct and oblique corrections, a tool for calculation of the oblique parameters is presented. This tool, named OPUCEM, brings together formulas from multiple physics models and provides an error-checking machinery to improve reliability of numerical results. It also sets a novel example for an "open-formula" concept, which is an attempt to improve the reliability and reproducibility of computations in scientific publications by encouraging the authors to open-source their numerical calculation programs. Finally, we demonstrate the use of OPUCEM in two detailed case studies related to the fourth Standard Model family. The first is a generic fourth family study to find relations between the parameters compatible with the EW precision data and the second is the particular study of the Flavor Democracy predictions for both Dirac and Majorana-type neutrinos.Comment: 10 pages, 19 figures, section 3 and 4 reviewed, results unchanged, typo correction

Resource provisioning in Science Clouds: Requirements and challenges

Cloud computing has permeated into the information technology industry in the last few years, and it is emerging nowadays in scientific environments. Science user communities are demanding a broad range of computing power to satisfy the needs of high-performance applications, such as local clusters, high-performance computing systems, and computing grids. Different workloads are needed from different computational models, and the cloud is already considered as a promising paradigm. The scheduling and allocation of resources is always a challenging matter in any form of computation and clouds are not an exception. Science applications have unique features that differentiate their workloads, hence, their requirements have to be taken into consideration to be fulfilled when building a Science Cloud. This paper will discuss what are the main scheduling and resource allocation challenges for any Infrastructure as a Service provider supporting scientific applications

Plotting the Differences Between Data and Expectation

This article proposes a way to improve the presentation of histograms where data are compared to expectation. Sometimes, it is difficult to judge by eye whether the difference between the bin content and the theoretical expectation (provided by either a fitting function or another histogram) is just due to statistical fluctuations. More importantly, there could be statistically significant deviations which are completely invisible in the plot. We propose to add a small inset at the bottom of the plot, in which the statistical significance of the deviation observed in each bin is shown. Even though the numerical routines which we developed have only illustration purposes, it comes out that they are based on formulae which could be used to perform statistical inference in a proper way. An implementation of our computation is available at https://github.com/dcasadei/psde .Comment: 10 pages, 7 figures. CODE: https://github.com/dcasadei/psd

Type Ia supernova parameter estimation: a comparison of two approaches using current datasets

By using the Sloan Digital Sky Survey (SDSS) first year type Ia supernova (SN Ia) compilation, we compare two different approaches (traditional \chi^2 and complete likelihood) to determine parameter constraints when the magnitude dispersion is to be estimated as well. We consider cosmological constant + Cold Dark Matter (\Lambda CDM) and spatially flat, constant w Dark Energy + Cold Dark Matter (FwCDM) cosmological models and show that, for current data, there is a small difference in the best fit values and $\sim$ 30% difference in confidence contour areas in case the MLCS2k2 light-curve fitter is adopted. For the SALT2 light-curve fitter the differences are less significant ($\lesssim$ 13% difference in areas). In both cases the likelihood approach gives more restrictive constraints. We argue for the importance of using the complete likelihood instead of the \chi^2 approach when dealing with parameters in the expression for the variance.Comment: 16 pages, 5 figures. More complete analysis by including peculiar velocities and correlations among SALT2 parameters. Use of 2D contours instead of 1D intervals for comparison. There can be now a significant difference between the approaches, around 30% in contour area for MLCS2k2 and up to 13% for SALT2. Generic streamlining of text and suppression of section on model selectio

ROOT - A C++ Framework for Petabyte Data Storage, Statistical Analysis and Visualization

ROOT is an object-oriented C++ framework conceived in the high-energy physics (HEP) community, designed for storing and analyzing petabytes of data in an efficient way. Any instance of a C++ class can be stored into a ROOT file in a machine-independent compressed binary format. In ROOT the TTree object container is optimized for statistical data analysis over very large data sets by using vertical data storage techniques. These containers can span a large number of files on local disks, the web, or a number of different shared file systems. In order to analyze this data, the user can chose out of a wide set of mathematical and statistical functions, including linear algebra classes, numerical algorithms such as integration and minimization, and various methods for performing regression analysis (fitting). In particular, ROOT offers packages for complex data modeling and fitting, as well as multivariate classification based on machine learning techniques. A central piece in these analysis tools are the histogram classes which provide binning of one- and multi-dimensional data. Results can be saved in high-quality graphical formats like Postscript and PDF or in bitmap formats like JPG or GIF. The result can also be stored into ROOT macros that allow a full recreation and rework of the graphics. Users typically create their analysis macros step by step, making use of the interactive C++ interpreter CINT, while running over small data samples. Once the development is finished, they can run these macros at full compiled speed over large data sets, using on-the-fly compilation, or by creating a stand-alone batch program. Finally, if processing farms are available, the user can reduce the execution time of intrinsically parallel tasks - e.g. data mining in HEP - by using PROOF, which will take care of optimally distributing the work over the available resources in a transparent way

Sqrt{shat}_{min} resurrected

We discuss the use of the variable sqrt{shat}_{min}, which has been proposed in order to measure the hard scale of a multi parton final state event using inclusive quantities only, on a SUSY data sample for a 14 TeV LHC. In its original version, where this variable was proposed on calorimeter level, the direct correlation to the hard scattering scale does not survive when effects from soft physics are taken into account. We here show that when using reconstructed objects instead of calorimeter energy and momenta as input, we manage to actually recover this correlation for the parameter point considered here. We furthermore discuss the effect of including W + jets and t tbar+jets background in our analysis and the use of sqrt{shat}_{min} for the suppression of SM induced background in new physics searches.Comment: 23 pages, 9 figures; v2: 1 figure, several subsections and references as well as new author affiliation added. Corresponds to published versio