Free Software Tools Research Articles

Plataforma informática para prevención de enfermedades en la florícola Produnorte S.A.

Producnorte S.A, una empresa privada que cultiva y exporta rosas de la más alta calidad, para satisfacer las necesidades de un mercado exclusivo, con lo que han logrado establecer relaciones a largo plazo con clientes. La aplicación web y móvil permite el control de datos de sanidad vegetal y cuenta con el registro de cumplimiento de trabajo, lo que permite optimizar tiempo en conocer las enfermedades de la plantación. El sistema fue desarrollado con herramientas de software libre. Se utilizó metodología ágil de desarrollo de software: SCRUM, la que permitió planificar el proyecto en pequeños bloques e ir mejorando constantemente, logrando resultados importantes como la maximización de la producción de rosas, y conocer el historial de cultivo para prevenir enfermedades.

Determination of the drag coefficient by analysing the trajectory of a football

Two different types of motion were analysed based on video footage using the free software tool named Tracker. One of them involved dropping the football vertically without any spin, the other type was the projectile motion resulted from a goalie punt. The analysis consisted of fitting the time dependence of the coordinates using a sixth order polynomial, then using these functions and other parameters to obtain the drag coefficient as a function of speed and Reynolds number. Similarly to previous works, the drag coefficient showed large differences for the different speeds. The irregularities and asymmetry of the ball also caused the results to be different for the different trials depending on the orientation of the ball, as well as the slight horizontal spin of the ball during its projectile motion. This method can prove to be a useful tool for further studies in a more controlled environment with higher quality new balls.

SSD - a free software for designing multimeric mono-, bi- and trivalent shRNAs.

RNA interference (RNAi) is a powerful gene silencing technology, widely used in analyses of reverse genetics, development of therapeutic strategies and generation of biotechnological products. Here we present a free software tool for the rational design of RNAi effectors, named siRNA and shRNA designer (SSD). SSD incorporates our previously developed software Strand Analysis to construct template DNAs amenable for the large scale production of mono-, bi- and trivalent multimeric shRNAs, via in vitro rolling circle transcription. We tested SSD by creating a trivalent multimeric shRNA against the vitellogenin gene of Apis mellifera. RT-qPCR analysis revealed that our molecule promoted a decrease in more than 50% of the target mRNA, in a dose-dependent manner, when compared to the control group. Thus, SSD software allows the easy design of multimeric shRNAs, for single or multiple simultaneous knockdowns, which is especially interesting for studies involving large amounts of double-stranded molecules.

Autodock Vina Adopts More Accurate Binding Poses but Autodock4 Forms Better Binding Affinity.

The binding pose and affinity between a ligand and enzyme are very important pieces of information for computer-aided drug design. In the initial stage of a drug discovery project, this information is often obtained by using molecular docking methods. Autodock4 and Autodock Vina are two commonly used open-source and free software tools to perform this task, and each has been cited more than 6000 times in the last ten years. It is of great interest to compare the success rate of the two docking software programs for a large and diverse set of protein-ligand complexes. In this study, we selected 800 protein-ligand complexes for which both PDB structures and experimental binding affinity are available. Docking calculations were performed for these complexes using both Autodock4 and Autodock Vina with different docking options related to computing resource consumption and accuracy. Our calculation results are in good agreement with a previous study that the Vina approach converges much faster than AD4 one. However, interestingly, AD4 shows a better performance than Vina over 21 considered targets, whereas the Vina protocol is better than the AD4 package for 10 other targets. There are 16 complexes for which both the AD4 and Vina protocols fail to produce a reasonable correlation with respected experiments so both are not suitable to use to estimate binding free energies for these cases. In addition, the best docking option for performing the AD4 approach is the long option. However, the short option is the best solution for carrying out Vina docking. The obtained results probably will be useful for future docking studies in deciding which program to use.

Application of automated electron microscopy imaging and machine learning to characterise and quantify nanoparticle dispersion in aqueous media.

SummaryFor many nanoparticle applications it is important to understand dispersion in liquids. For nanomedicinal and nanotoxicological research this is complicated by the often complex nature of the biological dispersant and ultimately this leads to severe limitations in the analysis of the nanoparticle dispersion by light scattering techniques. Here we present an alternative analysis and associated workflow which utilises electron microscopy. The need to collect large, statistically relevant datasets by imaging vacuum dried, plunge frozen aliquots of suspension was accomplished by developing an automated STEM imaging protocol implemented in an SEM fitted with a transmission detector. Automated analysis of images of agglomerates was achieved by machine learning using two free open‐source software tools: CellProfiler and ilastik. The specific results and overall workflow described enable accurate nanoparticle agglomerate analysis of particles suspended in aqueous media containing other potential confounding components such as salts, vitamins and proteins.Lay DescriptionIn order to further advance studies in both nanomedicine and nanotoxicology, we need to continue to understand the dispersion of nanoparticles in biological fluids. These biological environments often contain a number of components such as salts, vitamins and proteins which can lead to difficulties when using traditional techniques to monitor dispersion. Here we present an alternative analysis which utilises electron microscopy. In order to use this approach statistically relevant large image datasets were collected from appropriately prepared samples of nanoparticle suspensions by implementing an automated imaging protocol. Automated analysis of these images was achieved through machine learning using two readily accessible freeware; CellProfiler and ilastik. The workflow presented enables accurate nanoparticle dispersion analysis of particles suspended in more complex biological media.

333 Animal –GRIN a platform for animal genetic information

Abstract An information system, Animal-GRIN, has been constructed as part of the U.S., Brazilian, and Canadian livestock genetic resource programs. It is designed to provide information to gene bank managers, the research community, and livestock producers about livestock breeds and subpopulations acquired in gene bank collections. The system was developed using a range of free software tools, including: MySQL, Ruby on Rails, Java Script, etc. The system is dynamic and publically accessible (https://nrrc.ars.usda.gov/A-GRIN). Exemplary information in Animal-GRIN consists of: animal identifiers, number and type of samples in the collection, pedigrees, coefficients of genetic relationships between animals within a breed, breeding values, phenotypes, and geographic source. To meet the national need for the long term archiving of genomic information developed with public funds, Animal-GRIN was expanded to store and make publically available genomic information (SNP) from any SNP chip, including custom products. Researchers are encouraged to submit their data upon completion of their publically funded projects. With the drill down concept, users can search the database for genomic information, physical samples associated with the genomic information, and phenotypic information on specific animals. Once animals of interest are found, on-line tools enable users to request either germplasm samples or genomic data. Progress in meeting genetic security for a breed’s collection can also be viewed. To date the U.S. collection has 52,639 animals with almost a million samples representing 36 species, 167 breeds, and 331 subpopulations and these have been entered into Animal-GRIN. Genomic data has been acquired on 1,899 animals representing 36 breeds. The next phase of Animal-GRIN development will be development of landscape genomics components. Acquisition of germplasm samples and associated genomic information are a continuing effort.

Modeling Cell-Cell Interactions from Spatial Molecular Data with Spatial Variance Component Analysis

SummaryTechnological advances enable assaying multiplexed spatially resolved RNA and protein expression profiling of individual cells, thereby capturing molecular variations in physiological contexts. While these methods are increasingly accessible, computational approaches for studying the interplay of the spatial structure of tissues and cell-cell heterogeneity are only beginning to emerge. Here, we present spatial variance component analysis (SVCA), a computational framework for the analysis of spatial molecular data. SVCA enables quantifying different dimensions of spatial variation and in particular quantifies the effect of cell-cell interactions on gene expression. In a breast cancer Imaging Mass Cytometry dataset, our model yields interpretable spatial variance signatures, which reveal cell-cell interactions as a major driver of protein expression heterogeneity. Applied to high-dimensional imaging-derived RNA data, SVCA identifies plausible gene families that are linked to cell-cell interactions. SVCA is available as a free software tool that can be widely applied to spatial data from different technologies.

Implementación de un laboratorio de cómputo con software y hardware libres

Objetives: To implement a low cost computer laboratory, using free hardware such as Raspberry PI and free software such as Linux, for the support of primary schools that do not have the economic capacity to solve the purchase of a conventional computer laboratory, in order to increase the interest of students from first to 6th grade of the use of ICT in daily life. Methodology: An analysis of the different existing linux distributions for the raspberry PI was carried out, as well as the different free software programs that would be used in the classrooms, such as mathematics, history, reading, science and programming principles. Contribution: The use of free software tools in the classroom, is not only a matter of economy, but also the teaching of the 4 freedoms of free software, use, share, distribute, and the possibility of improving it knowing the source code. It also promotes collaborative work, and the use of free hardware has the advantage of technological independence.

Research on High Quality Bilingual Parallel Documents of Science and Technology Produced by Application Software Tools and Control Language

The aim of this study is to help English-based technicians produce high-quality translated documents with the help of free software tools (such as machine translation+post-translation compilation technology, computer-aided translation technology, etc.). This paper discusses a method of iteratively rewriting technical documents to help technicians generate more accurate bilingual parallel documents. It also studies how to use control language rules to rewrite technical documents to eliminate ambiguity and sentence complexity in order to improve the translatability of documents. Finally, a method is proposed to help users choose the most suitable machine translation engine.

Una experiencia docente de audición y creación musical mediante TIC con alumnado de altas capacidades intelectuales

La enseñanza musical ayuda al desarrollo de habilidades cognitivas en el alumnado. Comoafirman Villanueva y Molero, los estudiantes “que reciben una enseñanza musical, tienen mejor rendimiento y resultados en tareas espaciales, temporales, matemáticas, lectoras y de memoria verbal” (2014). Este efecto positivo, resulta especialmente relevante en alumnos con altas capacidades intelectuales (AACCII) ya que, además, la música ayuda a gestionar emociones y facilita la interacción de este tipo de estudiante con su entorno (Swanwick, 1988). La Universidad de Cádiz, en colaboración con la Junta de Andalucía, a través de su programa de Mentorías Universitarias, destinado al desarrollo de alumnado con altas capacidades intelectuales, ofrece cada año distintos itinerarios formativos para estudiantes de ESO, Bachillerato y Ciclos Formativos de Grado Medio y Superior en la provincia de Cádiz.Se trata de talleres que persiguen motivar a este perfil concreto de alumnado mediante laformación específica en distintas áreas de conocimiento y tutorización por parte de profesorado universitario en grupos reducidos. Este año, el Área de Didáctica de la Expresión Musical del Departamento de Didáctica de la Educación Física, Plástica y Musical de la Universidad de Cádiz ha ofrecido un taller titulado La audición y creación musical mediante TIC. Esta propuesta persigue alcanzar un objetivo principal: ofrecer a los estudiantes herramientas de software libre que les permitieran adquirir conocimientos y destrezas sobre el lenguaje musical de manera autónoma y desarrollar su creatividad musical. Para ello, se ha utilizado una metodología cualitativa, basada en el trabajo colaborativo entre losestudiantes (13 personas). Estos debían realizar actividades individuales de composición y grabación musical, que se presentaban ante el resto de alumnado y se modificaban siguiendo las indicaciones de todos los compañeros. Los resultados obtenidos han sido muy positivos: Hemos logrado alta implicación del alumnado y familiares, y los estudiantes han demostrado adquisición de conocimientos musicales y aplicación de los mismos en casos prácticos.

A New Relational Database Including Clinical Data and Myocardial Perfusion Imaging Findings in Coronary Artery Disease.

The aim of this study was to test a relational database including clinical data and imaging findings in a large cohort of subjects with suspected or known Coronary Artery Disease (CAD) undergoing stress single-photon emission computed tomography (SPECT) myocardial perfusion imaging. We developed a relational database including clinical and imaging data of 7995 subjects with suspected or known CAD. The software system was implemented by PostgreSQL 9.2, an open source object-relational database, and managed from remote by pgAdmin III. Data were arranged according to a logic of aggregation and stored in a schema with twelve tables. Statistical software was connected to the database directly downloading data from server to local personal computer. There was no problem or anomaly for database implementation and user connections to the database. The epidemiological analysis performed on data stored in the database demonstrated abnormal SPECT findings in 46% of male subjects and 19% of female subjects. Imaging findings suggest that the use of SPECT imaging in our laboratory is appropriate. The development of a relational database provides a free software tool for the storage and management of data in line with the current standard.

Computational Bottom-Up Vulnerability Indicator for Low-Income Flood-Prone Urban Areas

This study presents the implementation of a methodology for the formulation of a vulnerability indicator for low-income urban territories in flood-prone areas, for two flood types: Sudden and slow. The methodology developed a computational assessment tool based on the Multiple Correspondence Analysis and the framework for vulnerability analysis in sustainable science. This approach uses participatory mapping and on-site data. The data collection was easily implemented with free software tools to facilitate its use in low-income urban territories. The method combines the evaluation of experts using the of the traditional approach for the qualification of the variables of vulnerability in its three components (exposure, susceptibility, and resilience), and incorporates a computational method of the correspondence analysis family to formulate the indicators of vulnerability. The results showed that the multiple correspondence analysis is useful for the identification of the most representative variables in the vulnerability assessment, used for the construction of spatial disaggregated vulnerability indicators and therefore the development of vulnerability maps that will help in the short term in disaster risk management, urban planning, and infrastructure protection. In addition, the variables of the susceptibility component are the most representative regardless of the type of flooding, followed by the variables of the exposure component, for sudden flood-prone territories, and the resilience component for slow flood-prone territories. Our findings and the computational tool can facilitate the prioritization of improvement projects and flood risk management on a household, neighborhood, and municipal level.

Dasymetric Mapping Using UAV High Resolution 3D Data within Urban Areas

Multi-temporal analysis of census small-area microdata is hampered by the fact that census tract shapes do not often coincide between census exercises. Dasymetric mapping techniques provide a workaround that is nonetheless highly dependent on the quality of ancillary data. The objectives of this work are to: (1) Compare the use of three spatial techniques for the estimation of population according to census tracts: Areal interpolation and dasymetric mapping using control data—building block area (2D) and volume (3D); (2) demonstrate the potential of unmanned aerial vehicle (UAV) technology for the acquisition of control data; (3) perform a sensitivity analysis using Monte Carlo simulations showing the effect of changes in building block volume (3D information) in population estimates. The control data were extracted by a (semi)-automatic solution—3DEBP (3D extraction building parameters) developed using free open source software (FOSS) tools. The results highlight the relevance of 3D for the dasymetric mapping exercise, especially if the variations in height between building blocks are significant. Using low-cost UAV backed systems with a FOSS-only computing framework also proved to be a competent solution with a large scope of potential applications.

CALIMA: The semi-automated open-source calcium imaging analyzer

Background and objectiveEver since its discovery, calcium imaging has proven its worth in discovering new insights into the mechanisms of cellular communication. Yet, the analysis of the data generated by calcium imaging experiments demands a large amount of time from researchers. Tools enabling automated and semi-automated analysis are available, but often they allow automating only a part of the data analysis process. Therefore, we developed CALIMA (https://aethelraed.nl/calima), a free and open-source standalone software tool that provides an opportunity to quickly detect cells, to obtain the calcium spikes, and to determine the underlying network structure of neuronal cell cultures. MethodsOwing to the difference of Gaussians algorithm applied for the cell detection, CALIMA is able to detect regions of interest (ROIs) quickly. The z-scoring algorithm provides a means to set the requirements for spike detection, and the neuronal connections can be reconstructed by analyzing the cross-correlation between the cellular activity. We evaluated CALIMA's reliability, speed, and functionality with a special focus on neuronal cell detection and network reconstruction. The evaluation was performed by using real-life data such as a known example dataset (cultured primary rat cortical neurons, University of Pennsylvania) and by analyzing video graphic footage of in vitro brain cell samples (SH-SY5Y neuroblastoma cultures, one sample with synchronous neuron firing). The obtained results were compared to the corresponding outcomes observed on same datasets for other similar software solutions. Moreover, we compared the results of segmentation and peak detection analysis, the ones obtained using CALIMA and those acquired manually. ResultsCALIMA was able to detect the cells in the cultures within seconds. The average sensitivity was 82% across the datasets checked, comparing favorably with the alternative software solutions. Using the correct parameters, CALIMA's Ca-spikes detection sensitivity reached 96%. Lastly, neuronal networks were reconstructed by combining the data on the ROI's activity and the cell's positions, finding the most likely inter-cell connections. ConclusionsWe found that CALIMA proved to be a robust and fast tool to analyze the data of experiments for the digital reconstruction of the neuronal cellular network while being able to process the analysis steps with minimal user input required and in a time efficient manner.

PTMProphet: Fast and Accurate Mass Modification Localization for the Trans-Proteomic Pipeline.

Spectral matching sequence database search engines commonly used on mass spectrometry-based proteomics experiments excel at identifying peptide sequence ions, and in addition, possible sequence ions carrying post-translational modifications (PTMs), but most do not provide confidence metrics for the exact localization of those PTMs when several possible sites are available. Localization is absolutely required for downstream molecular cell biology analysis of PTM function in vitro and in vivo. Therefore, we developed PTMProphet, a free and open-source software tool integrated into the Trans-Proteomic Pipeline, which reanalyzes identified spectra from any search engine for which pepXML output is available to provide localization confidence to enable appropriate further characterization of biologic events. Localization of any type of mass modification (e.g., phosphorylation) is supported. PTMProphet applies Bayesian mixture models to compute probabilities for each site/peptide spectrum match where a PTM has been identified. These probabilities can be combined to compute a global false localization rate at any threshold to guide downstream analysis. We describe the PTMProphet tool, its underlying algorithms, and demonstrate its performance on ground-truth synthetic peptide reference data sets, one previously published small data set, one new larger data set, and also on a previously published phosphoenriched data set where the correct sites of modification are unknown. Data have been deposited to ProteomeXchange with identifier PXD013210.

Insight into structural features of phenyltetrazole derivatives as ABCG2 inhibitors for the treatment of multidrug resistance in cancer

ABSTRACT ABCG2 is the principal ABC transporter involved in the multidrug resistance of breast cancer. Looking at the current demand in the development of ABCG2 inhibitors for the treatment of multidrug-resistant cancer, we have explored structural requirements of phenyltetrazole derivatives for ABCG2 inhibition by combining classical QSAR, Bayesian classification modelling and molecular docking studies. For classical QSAR, structural descriptors were calculated from the free software tool PaDEL-descriptor. Stepwise multiple linear regression (SMLR) was used for model generation. A statistically significant model was generated and validated with different parameters (For training set: r = 0.825; Q 2 = 0.570 and for test set: r = 0.894, r2 pred = 0.783). The predicted model was found to satisfy the Golbraikh and Trospha criteria for model acceptability. Bayesian classification modelling was also performed (ROC scores were 0.722 and 0.767 for the training and test sets, respectively). Finally, the binding interactions of phenyltetrazole type inhibitor with the ABCG2 receptor were mapped with the help of molecular docking study. The result of the docking analysis is aligned with the classical QSAR and Bayesian classification studies. The combined modelling study will guide the medicinal chemists to act faster in the drug discovery of ABCG2 inhibitors for the management of resistant breast cancer.

Fast Proteome Identification and Quantification from Data-Dependent Acquisition–Tandem Mass Spectrometry (DDA MS/MS) Using Free Software Tools

The identification of nearly all proteins in a biological system using data-dependent acquisition (DDA) tandem mass spectrometry has become routine for organisms with relatively small genomes such as bacteria and yeast. Still, the quantification of the identified proteins may be a complex process and often requires multiple different software packages. In this protocol, I describe a flexible strategy for the identification and label-free quantification of proteins from bottom-up proteomics experiments. This method can be used to quantify all the detectable proteins in any DDA dataset collected with high-resolution precursor scans and may be used to quantify proteome remodeling in response to drug treatment or a gene knockout. Notably, the method is statistically rigorous, uses the latest and fastest freely-available software, and the entire protocol can be completed in a few hours with a small number of data files from the analysis of yeast.

Analysis of a Training Package for Law Enforcement to Conduct Open Source Research

Law enforcement officials (LEOs) in the UK conduct open source research (OSR) as part of their routine online investigations. OSR, in this instance, refers to publicly available information that is accessed via the Internet. As part of the research, identifying and tracing the electronic suspect (RITES) course provided by the UK's College of Policing, LEOs are introduced to the open source internet research tool (OSIRT); a free software tool designed to assist LEOs with OSR investigations. This article draws on analyses from questionnaires and observations from a RITES course; mapping them to Kirkpatrick's evaluation model. Results showed the positive impact the RITES course had in transferring knowledge back on-the-job, with LEOs applying knowledge learned to real-life investigative scenarios. Additionally, results showed OSIRT integrated both in the RITES course and into the LEOs investigative routine.

Implementation of an Online Software Tool for the Analytic Hierarchy Process (AHP-OS)

The Analytic Hierarchy Process (AHP) remains a popular multi-criteria decision method. The author has implemented a free, web-based AHP online system with noteworthy features, allowing for the detailed analysis of decision problems. Besides standard functions, like flexible decision hierarchies, support to improve inconsistent judgments, and alternative evaluation and sensitivity analysis, the software can handle group input, calculate group consensus based on Shannon ? and ?-entropy and estimate weight uncertainties based on randomized small variations of input judgments. In addition, different AHP judgment scales can be applied a posteriori and alternative evaluation can be done using the weighted sum (WSM) or weighted product model (WPM). This flexibility opens up opportunities to study decision projects under various parameters. The author’s intention was to provide a complete and free software tool for educational and research purposes where calculations and algorithms are well documented and all input data and results can be exported in an open format for further processing or presentation. The article describes the basic concept and structure of the software and the underlying mathematical algorithms and methods. Challenges and practical experiences during the implementation, validation and productive phase of the software are highlighted.

A modified stereographic projection approach and a free software tool for kinematic analysis of rock slope toppling failures

Toppling failure is one of the common instability modes of rock slopes. Up to date, the stereographic projection approach is still an indispensable tool for kinematic toppling failure analysis of rock slopes, since it is very convenient to perform kinematic analysis that is based on all discontinuity orientations, not just some representative values, and it visually shows the analysis results. This paper first discussed the limitations of the Goodman’s graphical approach for kinematic analysis of rock slope toppling failures, and then proposed a modified graphical approach and developed practical software in a spreadsheet of Microsoft Excel for practitioners. The discrepancy between the results obtained from Goodman’s approach and our modified approach was investigated with respect to different limit values of the intersection angle between the strikes of the slope and discontinuity (denoted as γTlim), cut slope dip angles, and discontinuity friction angles. The results showed that: (1) when γTlim = 30°, the designed slope according to the Goodman’s graphical approach might be conservative or unsafe, which is related to the cut slope angle and the friction angle of discontinuity; (2) when γTlim = 30° and cut slope dip angle ≤60°, with respect to discontinuity friction angle = 10°, 20°, 30° or 40°, the designed slope according to the Goodman’s graphical approach might be conservative; (3) when γTlim = 30° and cut slope dip angle ≥70°, with respect to discontinuity friction angle = 10°, 20°, 30° or 40°, the designed slope according to the Goodman’s graphical approach is possibly unsafe; (4) when γTlim = 30° and cut slope dip angle ≤60°, with the discontinuity friction angle increasing from 10° to 40°, the discrepancy of the critical regions determined by the two approaches increases with respect to the same values of cut slope dip angle; (5) when γTlim = 30° and cut slope dip angle ≥70°, with the discontinuity friction angle increasing from 10° to 40°, the discrepancy of the critical regions determined by the two approaches first increases and then decreases with respect to the same values of cut slope dip angle; and (6) therefore, when performing kinematic analysis of rock slope toppling failures, the modified graphical approach proposed in this paper is recommended.