User-friendly Software Package Research Articles

SolexaQA: At-a-glance quality assessment of Illumina second-generation sequencing data

BackgroundIllumina's second-generation sequencing platform is playing an increasingly prominent role in modern DNA and RNA sequencing efforts. However, rapid, simple, standardized and independent measures of run quality are currently lacking, as are tools to process sequences for use in downstream applications based on read-level quality data.ResultsWe present SolexaQA, a user-friendly software package designed to generate detailed statistics and at-a-glance graphics of sequence data quality both quickly and in an automated fashion. This package contains associated software to trim sequences dynamically using the quality scores of bases within individual reads.ConclusionThe SolexaQA package produces standardized outputs within minutes, thus facilitating ready comparison between flow cell lanes and machine runs, as well as providing immediate diagnostic information to guide the manipulation of sequence data for downstream analyses.

Optimal allocation of distributed generation using a two-stage multi-objective mixed-integer-nonlinear programming

Cost is one of the most essential factors that influence many decisions taken in the distribution system planning. In general, cost can be defined as everything that should be sacrificed to gain the desired results. This paper proposes a new two-stage methodology for distributed generation (DG) placement as an attractive option for distribution system planner. This method aims to minimize cost and maximize total system benefit (TSB). Optimal placement and size are obtained from total cost minimization mathematical problem which is solved in the first stage. For each DG cost characteristics and for each investment payback time, there is an optimal location and size. Then the optimal DG investment payback time results from the TSB maximization problem, which is solved in the second stage. The various DG technologies offer the opportunity of selecting the right energy solution at the right location. Five types of DG are tested to give system deciders some choices. Different system conditions are simulated to illustrate the effect of DG installation on the distribution system as well as the ability of the proposed methodology. A user-friendly software package has been developed to solve efficiently and quickly the two optimization mathematical problems. The proposed methodology has been tested on IEEE 30-bus test system. Copyright © 2010 John Wiley & Sons, Ltd.

Cheminformatic Tools for Medicinal Chemists

IntroductionCheminformatics can be broadly described as any attempttousechemicalinformationtoinfertherelationshipsbetweenor attributes of chemical structures. From a drug discoveryperspective, cheminformatic principles can be applied fromthe earliest stages of lead discovery (e.g., chemical similarityand library design) to lead optimization (e.g., QSAR studies)through to preclinical and clinical development (e.g., predic-tive toxicology). The popularity of cheminformatics and itsuse in academia and the pharmaceutical industry can beappreciated from the fact that at least five scientific journalsexist almost exclusively dedicated to the field (The Journal ofCheminformatics, The Journal of Chemical Information andModeling, The Journal of Computer-Aided Molecular Design,Molecular Bioinformatics,andQSAR and CombinatorialScience), and more than 15000 scientific journal articles havebeen published during just the last 5 years that describecheminformatic research. This intense interest in cheminfor-matics stems from the promise that, if underlying relation-ships between a given chemical structure and a host ofbiological end points exist and can be elucidated, drug dis-covery timelines can be significantly reduced. Given thepressure on the pharmaceutical industry to increase produc-tivity while decreasing costs, prior knowledge of which mole-cules have the highest probability of success (or at leastknowing which molecules are likely to fail) is worthy ofvigorous pursuit.Over the past decade there have been several significantadvancements in our understanding and application of che-minformatic principles. Approaches to measuring and com-paring chemical information have become both moresophisticated and accessible. For example, two of the mostpowerfulchemicalsimilaritymeasures(two-dimensional(2D)extended connectivity fingerprints and three-dimensional(3D) shape and electrostatic overlays) are available in user-friendly software packages from Scitegic (Accelrys) andOpeneye Scientific Software. Multiple methods for under-standing and predictingbioactivity have proven their robust-ness,includingpartialleast-squares(PLS),geneticalgorithms,Bayesian analyses, and Random Forest analyses. Our under-standing of molecular features or properties associated withcertain pharmacological end points has also dramaticallyincreased. For example, it has been widely recognized thatcertain structural features can be associated with toxicity,while other molecular properties (such as ClogP, molecularweight, and polar surface area) can be associated with oralbioavailability

Single-scattering properties of tri-axial ellipsoidal mineral dust aerosols: A database for application to radiative transfer calculations

This paper presents a user-friendly database software package of the single-scattering properties of individual dust-like aerosol particles for application to radiative transfer calculations in a spectral region from ultraviolet (UV) to far-infrared (far-IR). To expand the degree of morphological freedom of the commonly used spheroidal and spherical models, tri-axial ellipsoids were assumed to be the overall shape of dust-like aerosol particles. A combination of four computational methods, including the Lorenz–Mie theory, the T-matrix method, the discrete dipole approximation, and an improved geometric optics method, was employed to compute the phase matrix, extinction efficiency and single-scattering albedo of ellipsoids with various aspect ratios and sizes. The scattering property database was developed for 42 particle shapes specified in terms of two aspect ratios, 69 refractive indices and 471 size parameters. Additionally, accompanying software, based on interpolation, was developed to provide the single-scattering properties for user-specified aspect ratios, refractive indices and size parameters. The software package allows for the derivation of the bulk optical properties for a given distribution of particle microphysical parameters (i.e., refractive index, size parameter and two aspect ratios). The array-oriented single-scattering property data sets are stored in the NetCDF format.

E-Clic - easy climate data converter

There are an increasing number of studies that are now focussing on the influence of climate change on species’ distributions. However, access to predictive climatic datasets for future scenarios is difficult due to their specific formats and/or the need to be geographically downscaled. The TYN dataset is freely available to users and provides a synthetic format with several climatic models and IPCC future climate scenarios. Moreover, the CRU historical dataset (1901–2000) is also available which allows users to create baseline models for current climatic variables. E-clic is a free, user-friendly software package that offers three different ways to convert these two datasets into a spatially explicit raster format which is compatible with the most common geographic information systems and usable on different platforms.

Were genome‐wide linkage studies a waste of time? Exploiting candidate regions within genome‐wide association studies

A central issue in genome-wide association (GWA) studies is assessing statistical significance while adjusting for multiple hypothesis testing. An equally important question is the statistical efficiency of the GWA design as compared to the traditional sequential approach in which genome-wide linkage analysis is followed by region-wise association mapping. Nevertheless, GWA is becoming more popular due in part to cost efficiency: commercially available 1M chips are nearly as inexpensive as a custom-designed 10 K chip. It is becoming apparent, however, that most of the on-going GWA studies with 2,000-5,000 samples are in fact underpowered. As a means to improve power, we emphasize the importance of utilizing prior information such as results of previous linkage studies via a stratified false discovery rate (FDR) control. The essence of the stratified FDR control is to prioritize the genome and maintain power to interrogate candidate regions within the GWA study. These candidate regions can be defined as, but are by no means limited to, linkage-peak regions. Furthermore, we theoretically unify the stratified FDR approach and the weighted P-value method, and we show that stratified FDR can be formulated as a robust version of weighted FDR. Finally, we demonstrate the utility of the methods in two GWA datasets: Type 2 diabetes (FUSION) and an on-going study of long-term diabetic complications (DCCT/EDIC). The methods are implemented as a user-friendly software package, SFDR. The same stratification framework can be readily applied to other type of studies, for example, using GWA results to improve the power of sequencing data analyses.

As Time Goes by: A Simple Fool's Guide to Molecular Clock Approaches in Invertebrates*

Biologists have used a wide range of organisms to study the origin of taxa and their subsequent evolutionary change in space and time. One commonly used tool is the molecular clock approach, relating substitution rates of nucleotide or amino acid sequences to divergence times. The accuracy of the molecular clock, however, has long been subject to controversy, and numerous papers have addressed problems associated with estimating divergence times. Some workers pointed out a striking imbalance between sophisticated software algorithms used for molecular clock analyses on the one hand, and the poor data on the other hand. Moreover, there is often unease among workers relative to molecular clocks because of the controversy surrounding the approach, the complex mathematical background of many molecular clock tools, the still limited number of available, user-friendly software packages, the often confusing terminology of molecular clock approaches, and the general lack of reliable calibration points and/or external clock rates. The current review therefore briefly provides an overview of analytical strategies, covering approaches based on calibration points and/or bounds, approaches based on external clock rates, and approaches that attempt to estimate relative divergence times in the absence of information that can be used for estimating substitution rates. It also deals with major problems and pitfalls associated with data and analyses, including potential errors of calibration points and bounds, the performance of the gene(s) used, estimation of confidence limits, and misinterpretation of the results of clock analyses due to problems with sampling design. A substantial part of the review addresses the question of “universal” molecular clock rates and summarizes important biological and life history variables that account for deviations from rate constancy both between lineages and at different times within lineages. The usefulness of these factors is discussed within the framework of “trait-specific” molecular clock rates. One such clock rate is introduced here for the cytochrome c oxidase subunit I (COI) gene in small dioecious, tropical and subtropical Protostomia with a generation time of approximately one year. A flow chart is provided as a “simple fool's guide” to molecular clock analyses, together with a glossary of widely used terms in molecular clock approaches. Finally, step-by-step examples are provided for calculating divergence times in the caenogastropod subfamily Pyrgulinae based on both an internal calibration point and a “trait-specific” molecular clock rate, and it is demonstrated how a relative clock approach can be used for testing evolutionary hypotheses. Our review encourages a judicious use of molecular clock analyses in evolutionary studies of invertebrates by demonstrating their great potential on the one hand and (often-manageable) problems and pitfalls on the other hand.

Incremental Global Parameter Estimation in Dynamical Systems

Estimating the parameters of a dynamical system based on measurements is an important task in industrial and scientific practice. Since a model’s quality is directly linked to its parameter values, obtaining globally rather than locally optimal values is especially important in this context. In practice, however, local methods are used almost exclusively. This is mainly due to the high computational cost of global dynamic parameter estimation, which limits its application to relatively small problems comprising no more than a few equations and parameters. In addition, there is still a lack of software packages that allow global parameter estimation in dynamical systems without expert knowledge. Therefore, we propose an efficient computational method for obtaining globally optimal parameter estimates of dynamical systems using well-established, user-friendly software packages. The method is based on the so-called incremental identification procedure, in combination with deterministic global optimization tools for nonlinear programs.

User-Friendly Permeability Predicting Software for Technical Textiles

For simulating the injection stage of the manufacturing process of composite materials, the permeability of the textile is an important input parameter. The permeability of textiles can be determined experimentally. However, this is a time and resource consuming process and no standard procedure is yet available. In this paper, we will present a user-friendly software package to simulate the flow through a textile model and predict the permeability Results are presented for a woven fabric and two different non-crimp fabrics. The computed permeability values are compared with experimental results.

Recent developments on PLASMAKIN – a software package to model the kinetics in gas discharges

PLASMAKIN is a user-friendly software package to handle physical and chemical data used in plasma physics modeling and to compute the production and destruction terms in fluid models equations. These terms account for the particle or energy production and loss rates due to gas-phase and gas-surface reactions. The package has been restructured and expanded to (a) allow the simulation of atomic emission spectra taking into account line broadening processes and radiation trapping; (b) include a library to compute the electron kinetics; (c) include a database of species properties and reactions and, (d) include a Python interface to allow access from scripts and integration with other scientific software tools.

PDB Editor: a user-friendly Java-based Protein Data Bank file editor with a GUI

The Protein Data Bank file format is the format most widely used by protein crystallographers and biologists to disseminate and manipulate protein structures. Despite this, there are few user-friendly software packages available to efficiently edit and extract raw information from PDB files. This limitation often leads to many protein crystallographers wasting significant time manually editing PDB files. PDB Editor, written in Java Swing GUI, allows the user to selectively search, select, extract and edit information in parallel. Furthermore, the program is a stand-alone application written in Java which frees users from the hassles associated with platform/operating system-dependent installation and usage. PDB Editor can be downloaded from http://sourceforge.net/projects/pdbeditorjl/.

An implementation framework for wastewater treatment models requiring a minimum programming expertise

Mathematical modelling in environmental biotechnology has been a traditionally difficult resource to access for researchers and students without programming expertise. The great degree of flexibility required from model implementation platforms to be suitable for research applications restricts their use to programming expert users. More user friendly software packages however do not normally incorporate the necessary flexibility for most research applications. This work presents a methodology based on Excel and Matlab-Simulink for both flexible and accessible implementation of mathematical models by researchers with and without programming expertise. The models are almost fully defined in an Excel file in which the names and values of the state variables and parameters are easily created. This information is automatically processed in Matlab to create the model structure and almost immediate model simulation, after only a minimum Matlab code definition, is possible. The framework proposed also provides programming expert researchers with a highly flexible and modifiable platform on which to base more complex model implementations. The method takes advantage of structural generalities in most mathematical models of environmental bioprocesses while enabling the integration of advanced elements (e.g. heuristic functions, correlations). The methodology has already been successfully used in a number of research studies.

EGMlab, a scientific software for determining the gravity and gradient components from global geopotential models

Nowadays, Global Geopotential Models (GGMs) are used as a routine stage in the procedures to compute a gravimetric geoid. The GGMs based geoidal height also can be used for GPS/levelling and navigation purposes in developing countries which do not have accurate gravimetric geoid models. Also, the GGM based gravity anomaly including the digital elevation model can be used in evaluation and outlier detections schemes of the ground gravity anomaly data. Further, the deflection of vertical and gravity gradients components from the GGMs can be used for different geodetic and geophysical interpretation purposes. However, still a complete and user-friendly software package is not available for universities and geosciences communities. In this article, first we review the procedure for determination of the basic gravity field and gradient components from the GGMs, then general MATLAB based software is presented and applied as a sample case study for determination of gravity components based on the most recent EIGEN-GL04C GRACE model in Sweden.

Henry's law constant and related coefficients for aqueous hydrocarbons, CO 2 and H 2S over a wide range of temperature and pressure

This article presents three interrelated topics. First, the Henry's law constant (HLC) and its use are reviewed in a broader thermodynamic context reaching beyond the restricted image of HLC as a coefficient reflecting partitioning between liquid and vapor phases. The relationships of HLC to the vapor–liquid distribution coefficient and the air–water partition coefficient are discussed as well as the interrelation between expressions of HLC in terms of different concentration scales. Second, the previously published group contribution method for estimation of HLC of hydrocarbons [J. Sedlbauer, G. Bergin, V. Majer, AIChE J. 48 (2002) 2936] is extended by adding the newly determined parameters for CH 4, CO 2 and H 2S. Inclusion of these three major constituents of the natural gas makes the method more versatile in application to systems where oil and/or natural gas coexist with an aqueous phase. When establishing the parameters of the model the representative HLCs from literature were combined with the data on the derivative properties available over a wide range of conditions from the calorimetric and volumetric experiments. An attention is paid particularly to the effect of pressure on the HLC. Third, a convenient user-friendly software package is described allowing calculation of HLC and of other related coefficients over a wide range of temperature and pressure on the basis of the presented model. This package is available on request in an executable form on a shareware basis for non-commercial users.

DNA Origami Design of Dolphin-Shaped Structures with Flexible Tails

The DNA origami method allows the folding of long, single-stranded DNA sequences into arbitrary two-dimensional structures by a set of designed oligonucleotides. The method has revealed an unexpected strength and efficiency for programmed self-assembly of molecular nanostructures and makes it possible to produce fully addressable nanostructures with wide-reaching application potential within the emerging area of nanoscience. Here we present a user-friendly software package for designing DNA origami structures ( http://www.cdna.dk/origami ) and demonstrate its use by the design of a dolphin-like DNA origami structure that was imaged by high-resolution AFM in liquid. The software package provides automatic generation of DNA origami structures, manual editing, interactive overviews, atomic models, tracks the design history, and has a fully extendable toolbox. From the AFM images, it was demonstrated that different designs of the dolphin tail region provided various levels of flexibility in a predictable fashion. Finally, we show that the addition of specific attachment sites promotes dimerization between two independently self-assembled dolphin structures, and that these interactions stabilize the flexible tail.

Sampling and sensitivity analyses tools (SaSAT) for computational modelling

SaSAT (Sampling and Sensitivity Analysis Tools) is a user-friendly software package for applying uncertainty and sensitivity analyses to mathematical and computational models of arbitrary complexity and context. The toolbox is built in Matlab®, a numerical mathematical software package, and utilises algorithms contained in the Matlab® Statistics Toolbox. However, Matlab® is not required to use SaSAT as the software package is provided as an executable file with all the necessary supplementary files. The SaSAT package is also designed to work seamlessly with Microsoft Excel but no functionality is forfeited if that software is not available. A comprehensive suite of tools is provided to enable the following tasks to be easily performed: efficient and equitable sampling of parameter space by various methodologies; calculation of correlation coefficients; regression analysis; factor prioritisation; and graphical output of results, including response surfaces, tornado plots, and scatterplots. Use of SaSAT is exemplified by application to a simple epidemic model. To our knowledge, a number of the methods available in SaSAT for performing sensitivity analyses have not previously been used in epidemiological modelling and their usefulness in this context is demonstrated.

Evolutionary Minimum Cost Trajectory Planning for Industrial Robots

A general method for computing minimum cost trajectory planning for industrial robot manipulators is presented. The aim is minimization of a cost function with constraints namely joint positions, velocities, jerks and torques by considering dynamic equations of motion. A clamped cubic spline curve is used to represent the trajectory. This is a non-linear constrained optimization problem with five objective functions, 30 constraints and 144 variables. The cost function is a weighted balance of transfer time, mean average of actuators efforts and power, singularity avoidance, joint jerks and joint accelerations. The problem is solved by two evolutionary techniques such as Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and Differential Evolution (DE). Numerical applications for a six link robotic manipulator --- STANFORD robot (pick and place operation) and a two link planar manipulator (motion in the presence of obstacles) are illustrated. The results obtained from the Proposed techniques (NSGA-II and DE) are compared for different values of weighting coefficients. The influences of the algorithm parameters and weight factors on algorithm performance are analyzed. The DE algorithm converges quickly than NSGA-II. Also DE algorithm gives better results than NSGA-II in majority of cases. A comprehensive user-friendly general-purpose software package has been developed using VC++ to obtain the optimal solutions of any complex problem using DE algorithm.

“Space—The Final Frontier”

Regional planning agencies often project future income at the neighborhood level to determine future needs for transportation, jobs, social services, and amenities. Despite a decade of methodological advances regarding the importance of spatial autocorrelation in altering or reducing the reliability of regression estimates, few forecasters have tried to include such spatial relationships in their neighborhood-level projections. Part of the reason is that controlling for spatial autocorrelation is complex and can require expensive software. The authors use a free and user-friendly software package to estimate spatial effects in forecasting and then show how to develop and utilize proxy variables that can mitigate such autocorrelation. They illustrate how the failure to include such controls in Southern California could lead to overestimates of income in poor areas and hence a tendency to underserve needy areas.

TimeClust: a clustering tool for gene expression time series

TimeClust is a user-friendly software package to cluster genes according to their temporal expression profiles. It can be conveniently used to analyze data obtained from DNA microarray time-course experiments. It implements two original algorithms specifically designed for clustering short time series together with hierarchical clustering and self-organizing maps. TimeClust executable files for Windows and LINUX platforms can be downloaded free of charge for non-profit institutions from the following web site: http://aimed11.unipv.it/TimeClust.

Optimum static balancing of an industrial robot mechanism

Force balancing is a very important issue in mechanism design and has only recently been introduced to the designing step of robotic mechanisms. In creating the best robot design, the statical balancing plays a vital role because it reduces the required motor power. To get a simple and more-effective control system, elimination or significant reduction of the gravity load at a powered joint is an important one. With utilization of these objectives an optimization problem is formulated. The average force on the gripper in the working area is taken as an objective function. The design variables are lengths of the links, angles between them and stiffness of springs. This paper describes the use of conventional and evolutionary optimization techniques such as Newton's method (NM), conjugate gradient method (CGM), Genetic Algorithm (GA), Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and differential evolution (DE) to solve the above problem. An industrial robot with 6-degree-of-freedom (6-DOF) (APR 20) is considered as a numerical example. The robot has a spring balancing system that has to be optimized. The existing optimization model is improved by adding two new variables. Also, a comprehensive user-friendly general-purpose software package has been developed using VC++ to obtain the optimal parameters using the proposed DE algorithm. The methods used in this article can be applied to find out solutions for a wide range of similar problems without further simplifications.