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Background Advances in mobile sequencing devices and laptop performance make metagenomic sequencing and analysis in the field a technologically feasible prospect. However, metagenomic analysis pipelines are usually designed to run on servers and in the cloud. Results MAIRA is a new standalone program for interactive taxonomic and functional analysis of long read metagenomic sequencing data on a laptop, without requiring external resources. The program performs fast, online, genus-level analysis, and on-demand, detailed taxonomic and functional analysis. It uses two levels of frame-shift-aware alignment of DNA reads against protein reference sequences, and then performs detailed analysis using a protein synteny graph. Conclusions We envision this software being used by researchers in the field, when access to servers or cloud facilities is difficult, or by individuals that do not routinely access such facilities, such as medical researchers, crop scientists, or teachers.

Nuclear magnetic resonance (NMR) spectroscopy is a method of choice to study the dynamics and determine the atomic structure of macromolecules in solution. The standalone program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of nuclear Overhauser enhancement (NOE) data and structure calculation is well established in the NMR community. To ultimately provide a perfectly transparent and easy to use service, we designed an online user interface to ARIA with additional functionalities. Data conversion, structure calculation setup and execution, followed by interactive visualization of the generated 3D structures are all integrated in ARIAweb and freely accessible at https://ariaweb.pasteur.fr.

There is an accelerating interest in practical applications of alchemical free energy methods to problems in protein design, constant pH simulations, and especially computer-aided drug design. In the present paper, we describe a basic lambda dynamics engine (BLaDE) that enables alchemical free energy simulations, including multisite λ dynamics (MSλD) simulations, on graphical processor units (GPUs). We find that BLaDE is 5 to 8 times faster than the current GPU implementation of MSλD-based free energy calculations in CHARMM. We also demonstrate that BLaDE running standard molecular dynamics attains a performance competitive with and sometimes exceeding that of the highly optimized OpenMM GPU code. BLaDE is available as a standalone program and through an API in CHARMM.

Background The Sequence Alignment/Map Format Specification (SAM) is one of the most widely adopted file formats in bioinformatics and many researchers use it daily. Several tools, including most high-throughput sequencing read aligners, use it as their primary output and many more tools have been developed to process it. However, despite its flexibility, SAM encoded files can often be difficult to query and understand even for experienced bioinformaticians. As genomic data are rapidly growing, structured, and efficient queries on data that are encoded in SAM/BAM files are becoming increasingly important. Existing tools are very limited in their query capabilities or are not efficient. Critically, new tools that address these shortcomings, should not be able to support existing large datasets but should also do so without requiring massive data transformations and file infrastructure reorganizations. Results Here we introduce SamQL, an SQL-like query language for the SAM format with intuitive syntax that supports complex and efficient queries on top of SAM/BAM files and that can replace commonly used Bash one-liners employed by many bioinformaticians. SamQL has high expressive power with no upper limit on query size and when parallelized, outperforms other substantially less expressive software. Conclusions SamQL is a complete query language that we envision as a step to a structured database engine for genomics. SamQL is written in Go, and is freely available as standalone program and as an open-source library under an MIT license, https://github.com/maragkakislab/samql/.

Genomes and transcriptomes are now typically sequenced by individual laboratories but analyzing them often remains challenging. One essential step in many analyses lies in identifying orthologs—corresponding genes across multiple species—but this is far from trivial. The Orthologous MAtrix (OMA) database is a leading resource for identifying orthologs among publicly available, complete genomes. Here, we describe the OMA pipeline available as a standalone program for Linux and Mac. When run on a cluster, it has native support for the LSF, SGE, PBS Pro, and Slurm job schedulers and can scale up to thousands of parallel processes. Another key feature of OMA standalone is that users can combine their own data with existing public data by exporting genomes and precomputed alignments from the OMA database, which currently contains over 2100 complete genomes. We compare OMA standalone to other methods in the context of phylogenetic tree inference, by inferring a phylogeny of Lophotrochozoa, a challenging clade within the protostomes. We also discuss other potential applications of OMA standalone, including identifying gene families having undergone duplications/losses in specific clades, and identifying potential drug targets in nonmodel organisms. OMA standalone is available under the permissive open source Mozilla Public License Version 2.0., Genome Research, 29 (7), ISSN:1088-9051, ISSN:1549-5469

In this study, the effectiveness of the Observed Protective Behaviors behaviors test, a single-session, disclosure-focused, in situ skills training (IST), was evaluated as a standalone program (IST only) or as a booster to the child protective education program, Learn to be safe with Emmy and friends ™ (program + IST). Participants included 281 Year 1 children (5–7 years; 52% male), randomly assigned to IST only, program + IST, program only or waitlist, and followed across 6 months. At each assessment, children completed interviews to assess their intention and confidence to disclose unsafe situations (disclosure intentions and confidence) and their ability to identify unsafe situations (safety identification skills). Children also reported their anxiety symptoms to assess for a possible iatrogenic effect. The IST-only condition was effective, with children showing increased disclosure intentions relative to waitlist children. The program + IST condition was also effective, with children showing increased disclosure intentions relative to children in the waitlist or program-only conditions as well as greater increases in disclosure confidence relative to waitlist children. No differences were observed between conditions in children’s safety identification skills, and no iatrogenic effect on anxiety was found. Future research may seek to develop an IST that will also boost children’s safety identification skills.

The increasing availability of extensive collections of chemical compounds associated with experimental data provides an opportunity to build predictive quantitative structure-activity relationship (QSAR) models using machine learning (ML) algorithms. These models can promote data-driven decisions and have the potential to speed up the drug discovery process and reduce their failure rates. However, many essential aspects of data preparation and modeling are not available in any standalone program. Here, we developed an automated framework for the curation of chemogenomics data and to develop QSAR models for virtual screening using the open-source KoNstanz Information MinEr (KNIME) program. The workflow includes four modules: (i) dataset preparation and curation; (ii) chemical space analysis and structure-activity relationships (SAR) rules; (iii) modeling; and (iv) virtual screening (VS). As case studies, we applied these workflows to four datasets associated with different endpoints. The implemented protocol can efficiently curate chemical and biological data in public databases and generates robust QSAR models. We provide scientists a simple and guided cheminformatics workbench following the best practices widely accepted by the community, in which scientists can adapt to solve their research problems. The workflows are freely available for download at GitHub and LabMol web portals.

Programming for a diverse set of compute accelerators in addition to the CPU is a challenge. Maintaining separate source code for each architecture would require lots of effort, and development of new algorithms would be daunting if it had to be repeated many times. Fortunately there are several portability technologies on the market such as Alpaka, Kokkos, and SYCL. These technologies aim to improve the developer productivity by making it possible to use the same source code for many different architectures. In this paper we use heterogeneous pixel reconstruction code from the CMS experiment at the CERNL LHC as a realistic use case of a GPU-targeting HEP reconstruction software, and report experience from prototyping a portable version of it using Kokkos. The development was done in a standalone program that attempts to model many of the complexities of a HEP data processing framework such as CMSSW. We also compare the achieved event processing throughput to the original CUDA code and a CPU version of it., Comment: Submitted to 25th International Conference on Computing in High-Energy and Nuclear Physics (vCHEP 2021)

We present SMILES-embeddings derived from the internal encoder state of a Transformer [1] model trained to canonize SMILES as a Seq2Seq problem. Using a CharNN [2] architecture upon the embeddings results in higher quality interpretable QSAR/QSPR models on diverse benchmark datasets including regression and classification tasks. The proposed Transformer-CNN method uses SMILES augmentation for training and inference, and thus the prognosis is based on an internal consensus. That both the augmentation and transfer learning are based on embeddings allows the method to provide good results for small datasets. We discuss the reasons for such effectiveness and draft future directions for the development of the method. The source code and the embeddings needed to train a QSAR model are available on https://github.com/bigchem/transformer-cnn. The repository also has a standalone program for QSAR prognosis which calculates individual atoms contributions, thus interpreting the model’s result. OCHEM [3] environment (https://ochem.eu) hosts the on-line implementation of the method proposed.

This paper presents educational softwarebased on MATLAB and a Graphical User Interface (GUI). This educational softwareconsists of three subjects; electromagnetic, communication engineering andpower engineering. MATLAB m-files are developed based on the requirements inthe subjects. Then, its GUI are developed and integrated with the m-files forease of use. In this software, user is able to visualize the subjects from theplots, graphs, and images and obtain the answer automatically. User also doesnot need to install MATLAB in his/her Personal Computer (PC) because thissoftware is developed with standalone program which allow user to use thesoftware without installing Matlab. This software can be used by lecturers asteaching aid and self-learning materials among students, thus, help user toachieve better understanding on electrical engineering subjects. It is alsofound that this software has obtained positive feedback from lecturers andstudents as it attracts students in learning the subjects. &nbsp

In this paper, an educational software was developed using MATLAB and its Graphical User Interface (GUI). This interactive and user-friendly software focuses on three subjects which are electromagnetic, communication engineering and power engineering. The user uses MATLAB GUI in designing the educational software and compiled together with M-file program to develop a standalone program. Standalone program was created to ease the students to use this educational software without installing MATLAB software in their personal computer. This software may help user to get a better understanding on electrical engineering subjects such as electromagnetic, communication engineering and power engineering.

As a fast-growing field with widespread impact on economy and its promising hiring potential, Data Science has been enthusiastically sought-out by many disciplines in the academia, including Mathematics, Statistics, Library Science, Management Information Systems, as well as Computer Science, as an attracting area for recruiting students, soliciting grants, and expanding their existing programs. Although some standalone programs in Data Science have been established around the country, many institutions encounter the challenges in balancing the curricula among different disciplines, allocating new resources, and cooperating with the existing majors regarding enrollment management, student advising, and faculty preparation. In this paper, a strategy-based framework is proposed for those who have limited resources of all kinds to introduce Data Science through their existing Computer Science programs at a baccalaureate level with a minimum curriculum disruption. Instead of a standalone program, to embed Data Science into Computer Science education is demonstrated to be a practical, effective, cost-saving approach based on an extensive study of the synergy between Data Science and Computer Science education. While the proposed framework is not a one-size-fits-all approach, it provides a doable route for blending Data Science into Computer Science education in systematic ways. It has become the consensus that an adequate exposure to Data Science will better prepare computer science students for taking the challenges in this ever-changing, data embraced world.

This paper describes Stata command lclogit2, an enhanced version of lclogit (Pacifico and Yoo, 2013). Like its predecessor, lclogit2 uses the Expectation-Maximization (EM) algorithm to estimate latent class conditional logit (LCL) models. But it executes the EM algorithm's core algebraic operations in Mata, and runs considerably faster as a result. It also allows linear constraints on parameters to be imposed in a more convenient and flexible manner. It comes with parallel command lclogitml2, a new standalone program that uses gradient-based algorithms to estimate LCL models. Both lclogit2 and lclogitml2 are supported by a new postestimation tool, lclogitwtp2, that evaluates willingness-to-pay measures implied by estimated LCL models.

In this article, we introduce an efficient global-minimum structural search program named Tsinghua Global Minimum 2 (TGMin-2), which is the successor of the original TGMin algorithm that was developed in our group in 2011. We have introduced a number of new features and improvements into TGMin-2, including a symmetric structure generation algorithm that can produce good initial seeds for small- and medium-size clusters, the duplicated structure identification algorithm, and the improved structure adaption algorithm that was implemented in the original TGMin code. To predict the simulated photoelectron spectrum (PE spectrum) automatically, we also implemented a standalone program named AutoPES (Auto Photoelectron Spectroscopy), which can be used to simulate PE spectra and compare them with experimental results automatically. We have demonstrated that TGMin-2 and AutoPES are powerful tools for studying free and surface-supported molecules, clusters, and nanoclusters. © 2018 Wiley Periodicals, Inc.

In this paper, we evaluate using genotype‐by‐sequencing (GBS) data to perform parentage assignment in lieu of traditional array data. The use of GBS data raises two issues: First, for low‐coverage (e.g., 2×) GBS data performs similarly to array data and requires only a small number of markers to correctly assign parents and (b) low‐coverage GBS data (as low as 0.1×) can also be used, provided that it is obtained across a large number of markers. When analysing the low‐coverage GBS data, we also found a high number of false positives if the true parent is not contained within the list of candidate parents, but that this false positive rate can be greatly reduced by hand tuning the assignment threshold. We provide this parentage assignment method as a standalone program called AlphaAssign.

Summary Quantitative aspects of the study of animal and human behaviour are increasingly relevant to test hypotheses and find empirical support for them. At the same time, photo and video cameras can store a large number of video recordings and are often used to monitor the subjects remotely. Researchers frequently face the need to code considerable quantities of video recordings with relatively flexible software, often constrained by species-specific options or exact settings. BORIS is a free, open-source and multiplatform standalone program that allows a user-specific coding environment to be set for a computer-based review of previously recorded videos or live observations. Being open to user-specific settings, the program allows a project-based ethogram to be defined that can then be shared with collaborators, or can be imported or modified. Projects created in BORIS can include a list of observations, and each observation may include one or two videos (e.g. simultaneous screening of visual stimuli and the subject being tested; recordings from different sides of an aquarium). Once the user has set an ethogram, including state or point events or both, coding can be performed using previously assigned keys on the computer keyboard. BORIS allows definition of an unlimited number of events (states/point events) and subjects. Once the coding process is completed, the program can extract a time-budget or single or grouped observations automatically and present an at-a-glance summary of the main behavioural features. The observation data and time-budget analysis can be exported in many common formats (TSV, CSV, ODF, XLS, SQL and JSON). The observed events can be plotted and exported in various graphic formats (SVG, PNG, JPG, TIFF, EPS and PDF).

Software implementations of thermodynamic property routines for ammonia-water mixtures are developed for refrigeration and air-conditioning applications. Saturation correlations are employed to identify single-phase state points, yielding up to a 5-fold reduction in property evaluation time. A run-time database of previously evaluated state points is implemented to improve initial guesses for iterative property evaluation, reducing property evaluation time by 45% in a representative study. The property routines are implemented in a standalone program and as a compiled routine for use in MATLAB® and Simulink®. Both implementations perform property evaluations significantly faster than existing software packages. Program performance is measured on a 2.2 GHz machine, and average individual state point evaluation times were found to range from 50 to 930 µs, depending on the provided input properties. Additionally, a segmented, transient, ammonia-water absorber model is developed in Simulink® to assess the use of the property routines for practical engineering calculations. The proposed computational techniques can be applied to accelerate property evaluations for other mixtures.

Student success is one of the most widely discussed topics in the higher education literature. One understudied factor that may have a significant impact on student success is the effect of co-locating two different undergraduate programs - specifically, Computer Science (CS) and Information Technology (IT) - in the same department. In this paper, we examine student data from the IT and CS undergraduate programs at a large, public university to identify and compare the paths of IT and CS students, who started the program in Fall 2008 and dropped out, changed their major, or successfully completed the program by Summer 2013. We also conducted an open-ended survey of 165 IT and CS students to determine their perceptions of the two programs. Our results suggest a tiered relationship between the two programs, where CS appears to be a more volatile and rigorous of a major in terms of student pathways and perceptions. We conclude that social comparisons that occur due to the way these programs were established at the target university contribute to this imbalance. Based on our analyses, we propose measures to mitigate negative social comparisons between the two programs and make IT a standalone program contributing to student success.

Background Third generation sequencing technologies generate long reads that exhibit high error rates, in particular for insertions and deletions which are usually the most difficult errors to cope with. The only exact algorithm capable of aligning sequences with insertions and deletions is a dynamic programming algorithm. Results In this note, for the sake of efficiency, we consider dynamic programming in a band. We show how to choose the band width in function of the long reads’ error rates, thus obtaining an \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$O(N^{\frac {3}{2}})$\end{document}O(N32) algorithm in space and time. We also propose a procedure to decide whether this algorithm, when applied to semi-global alignments, provides the optimal score. Conclusions We suggest that dynamic programming in a band is well suited to the problem of aligning long reads between themselves and can be used as a core component of methods for obtaining a consensus sequence from the long reads alone. The function implementing the dynamic programming algorithm in a band is available, as a standalone program, at: https://forgemia.inra.fr/jean-francois.gibrat/BAND_DYN_PROG.git

Traditionally, we have two possibilities to design tools for program comprehension and analysis. The first option is to create a standalone program, independent of any source code editor. This way, the act of source code editing is separated from the act of viewing the code analysis results. The second option is to create a plugin for a specific IDE (integrated development environment) - in this case, a separate version must be created for each IDE. We propose an approach where information about source code elements is written directly into source files as annotations or special comments. Before committing to a version control system, the annotations are removed from the source code to avoid code pollution. We briefly evaluate the approach and delineate its limitations.

Summary Human observation is expensive and limits the breadth of data collection. For this reason, remotely placed video cameras are increasingly used to monitor animals. One drawback of field-based video recordings is extensive review time. Computer vision can mitigate this cost and enhance data collection by extracting biological information from images with minimal time investment. MotionMeerkat is a new standalone program that identifies motion events from a video stream. After running a video, the user reviews a folder of candidate motion frames for the target organism. This tool reduces the time needed to review videos and accommodates a variety of inputs. I tested MotionMeerkat using hummingbird–plant videos recorded in a tropical montane forest. To validate the optimal parameter set for finding motion events, I counted hummingbirds observed from direct video review compared to events found in images returned from MotionMeerkat. To show the generality of the approach, MotionMeerkat was tested on a set of terrestrial and underwater videos. To assess the performance of the background subtraction for further image analysis, I hand counted the number of frames with target organisms and compared them to the MotionMeerkat output. MotionMeerkat was highly successful in finding motion events and often reduced the number of frames needed to capture hummingbird visitation by over 90%. Both background approaches effectively found a variety of organisms in ecological videos. I provide general recommendations for parameter settings and extending this approach in the future.

A worm is a standalone program, which is self-replicating malware that distributes itself to other computers and networks. An Internet worm can spread across the network and infect millions of computers in very little time. Damages caused by such attacks are considered very high. Worms affect the network packet and its performance. In this paper, different methods are analyzed to detect Internet worms. Algorithms like Bayesian Network, Back Propagation Neural Network etc., were used to develop some detection techniques. These techniques led to a better understanding of the spreading of worms and are also successful in identifying the internet worms. They were found to be effective in preventing network attacks with high accuracy. The proposed techniques are low cost and provide counter measures to control the spread of internet worms.

Current architecture complexity requires fine tuning of compiler and runtime parameters to achieve full potential performance. Autotuning substantially improves default parameters in many scenarios but it is a costly process requiring a long iterative evaluation. We propose an automatic piecewise autotuner based on CERE Codelet Extractor and REplayer. CERE decomposes applications into small pieces called codelets: each codelet maps to a loop or to an OpenMP parallel region and can be replayed as a standalone program. Codelet autotuning achieves better speedups at a lower tuning cost. By grouping codelet invocations with the same performance behavior, CERE reduces the number of loops or OpenMP regions to be evaluated. Moreover unlike whole-program tuning, CERE customizes the set of best parameters for each specific OpenMP region or loop. We demonstrate CERE tuning of compiler optimizations, number of threads and thread affinity on a NUMA architecture. On average over the NAS 3.0 benchmarks, we achieve a speedup of 1.08$$\times $$ after tuning. Tuning a single codelet is 13$$\times $$ cheaper than whole-program evaluation and estimates the tuning impact on the original region with a 94.7i?ź% accuracy. On a Reverse Time Migration RTM proto-application we achieve a 1.11$$\times $$ speedup with a 200$$\times $$ cheaper exploration.

The common approach to electronic publishing three-dimensional biological data in peer-reviewed journals or for disseminating such data within the scientific community has historically required the writing of a two dimensional flat and non-interactive document. The frequent limit on the number of two dimensional color figures permitted in journals further reduces the opportunities for the provision of visualizations. Often the targeted readers of these documents are not expert in the gathering and manipulation of the fundamental data from which the document was provided. For example, three-dimensional protein structures and complexes require the downloading of coordinates from the PDB [1] and then the knowledge and skill to operate a standalone program to simply reproduce the view corresponding to the figure in question and to further interpret it. Further data, such as protein sequences, parts of the electron density [2], etc., may also need to be obtained from remote databases and manipulated to interpret the results and conclusions of the underlying publication. This approach is clearly sub-optimal for scientists who have no experience in protein structure and its visualization. A breakthrough in the ability to collate and integrate pertinent data types and annotations relating to such data into one file that is compact and platform-independent was the iSee platform [3]. In this approach, arbitrary numbers of three-dimensional structural visualizations are possible and the renditions are embedded via hyperlinks in a textual annotation akin to a standard scientific publication. Previously these so-called iSee ‘datapacks’ could be read and viewed using freely-available browser software. A number of other approaches to visualize three-dimensional structures within the context of text have been made since iSee was developed (e.g. [4]–[6]). However, neither these nor iSee have been able to provide full integration within the requirements of peer-reviewed publications and to support both the web delivery of an electronic publication and the local file delivery in a consistent manner. We have recognized that there is a clear requirement to improve the integration and delivery for publication and general dissemination of this type of work. In this overview we provide details of our activeICM approach for the peer-reviewed publishing and sharing of integrated and interactive iSee datapacks, or 3D documents, which is the core technology of the PLoS ONE Collection of which this overview paper is part of.

ORBKIT is a toolbox for postprocessing electronic structure calculations based on a highly modular and portable Python architecture. The program allows computing a multitude of electronic properties of molecular systems on arbitrary spatial grids from the basis set representation of its electronic wavefunction, as well as several grid-independent properties. The required data can be extracted directly from the standard output of a large number of quantum chemistry programs. ORBKIT can be used as a standalone program to determine standard quantities, for example, the electron density, molecular orbitals, and derivatives thereof. The cornerstone of ORBKIT is its modular structure. The existing basic functions can be arranged in an individual way and can be easily extended by user-written modules to determine any other derived quantity. ORBKIT offers multiple output formats that can be processed by common visualization tools (VMD, Molden, etc.). Additionally, ORBKIT possesses routines to order molecular orbitals computed at different nuclear configurations according to their electronic character and to interpolate the wavefunction between these configurations. The program is open-source under GNU-LGPLv3 license and freely available at https://github.com/orbkit/orbkit/. This article provides an overview of ORBKIT with particular focus on its capabilities and applicability, and includes several example calculations. © 2016 Wiley Periodicals, Inc.

High-throughput sequencing (HTS) technologies are providing an unprecedented capacity for data generation, and there is a corresponding need for efficient data exploration and analysis capabilities. Although most existing tools for HTS data analysis are developed for either automated (e.g. genotyping) or visualization (e.g. genome browsing) purposes, such tools are most powerful when combined. For example, integration of visualization and computation allows users to iteratively refine their analyses by updating computational parameters within the visual framework in real-time. Here we introduce the second version of the Savant Genome Browser, a standalone program for visual and computational analysis of HTS data. Savant substantially improves upon its predecessor and existing tools by introducing innovative visualization modes and navigation interfaces for several genomic datatypes, and synergizing visual and automated analyses in a way that is powerful yet easy even for non-expert users. We also present a number of plugins that were developed by the Savant Community, which demonstrate the power of integrating visual and automated analyses using Savant. The Savant Genome Browser is freely available (open source) at www.savantbrowser.com.

Eucb is a standalone program for geometrical analysis of molecular dynamics trajectories of protein systems. The program is written in GNU C++ and it can be installed in any operating system running a C++ compiler. The program performs its analytical tasks based on user supplied keywords. The source code is freely available from http://stavrakoudis.econ.uoi.gr/eucb under LGPL 3 license. Program summary Program title: Eucb Catalogue identifier: AEIC_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEIC_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 31 169 No. of bytes in distributed program, including test data, etc.: 297 364 Distribution format: tar.gz Programming language: GNU C++ Computer: The tool is designed and tested on GNU/Linux systems Operating system: Unix/Linux systems RAM: 2 MB Supplementary material: Sample data files are available Classification: 3 Nature of problem: Analysis of molecular dynamics trajectories. Solution method: The program finds all possible interactions according to input files and the user instructions. Then it reads all the trajectory frames and finds those frames in which these interactions occur, under certain geometrical criteria. This is a blind search, without a priori knowledge if a certain interaction occurs or not. The program exports time series of these quantities (distance, angles, etc.) and appropriate descriptive statistics. Running time: Depends on the input data and the required options.

Motivation: PSORTb has remained the most precise bacterial protein subcellular localization (SCL) predictor since it was first made available in 2003. However, the recall needs to be improved and no accurate SCL predictors yet make predictions for archaea, nor differentiate important localization subcategories, such as proteins targeted to a host cell or bacterial hyperstructures/organelles. Such improvements should preferably be encompassed in a freely available web-based predictor that can also be used as a standalone program. Results: We developed PSORTb version 3.0 with improved recall, higher proteome-scale prediction coverage, and new refined localization subcategories. It is the first SCL predictor specifically geared for all prokaryotes, including archaea and bacteria with atypical membrane/cell wall topologies. It features an improved standalone program, with a new batch results delivery system complementing its web interface. We evaluated the most accurate SCL predictors using 5-fold cross validation plus we performed an independent proteomics analysis, showing that PSORTb 3.0 is the most accurate but can benefit from being complemented by Proteome Analyst predictions. Availability: http://www.psort.org/psortb (download open source software or use the web interface). Contact: psort-mail@sfu.ca Supplementary Information: Supplementary data are availableat Bioinformatics online.

This paper presents a user-friendly learning software using MATLAB and its Graphical User Interface (GUI) to help student in achieving a better understanding in electrical engineering subjects. Currently, this educational software is designed for three subjects; electromagnetic, digital communication and power engineering. The m-files are developed and their graphical user interfaces (GUIs) are designed for ease of use. The standalone program is also developed; thus, user does not need to install MATLAB in their Personal Computer (PC) in order to use this educational software.

Electron microscopy has been used to measure the mass of biological nanoparticles since the early 60s, and is the only way to obtain the mass of large structures or parameters such as the mass-per-length of filaments. The ability of this method to sort heterogeneous samples both in terms of mass and shape promises to make it a key tool for proteomics down to the single cell level. A new multiplatform software package, MASDET, that can be run under MATLAB or as a standalone program is described. Based on a user-friendly graphical interface MASDET streamlines mass evaluation and greatly increases the speed of required optimisation procedures. Importantly, the immediate application of Monte-Carlo simulations to describe multiple scattering is possible, allowing the mass analysis of thicker samples and the generation of mass thickness maps.

The Internet guide for dentistry Email is a crucial communication tool and everyone who uses it should have a good understanding of the email program that they use to send and receive email. In some cases this will be built into their dental system software and for others it may be a web-based email account using the Internet Explorer web browser. In this section we look at the workings of the most popular standalone program, Outlook Express, and discuss good email practice for home and work.

RNA interference (RNAi) is a popular and effective method for silencing gene expression. siRNAs should be gene-specific and effective to achieve specific and potent gene silencing. However, most currently available siRNA design programs are web-based programs that either require each sequence be submitted individually, making large-batch analyses difficult to conduct, or only provide limited options for searching off-target candidates (e.g. NCBI-BLAST). We have developed a stand-alone, enhanced RNAi design program that overcomes these shortcomings. We have implemented WU-BLAST, FASTA and SSEARCH homology searches for siRNA candidates to improve gene specific siRNA selection and to identity siRNA candidates that could lead to off-target gene silencing. We also included many new features such as siRNA score calculation and calculation of siRNA internal stability to help select highly potent siRNAs. This program is freely available for academic and commercial use (ftp://ftp.systemsbiology.net/pub/blin/SiRNA/), and can be installed and run on any Linux machine. Our program automates the search for siRNAs and the resulting data files including a list of siRNA primers with scores and database search results for each siRNA candidate are stored locally for easy retrieval and inspection when needed.

Being involved in many important biological processes, miRNAs can regulate gene expression by targeting mRNAs to facilitate their degradation or translational inhibition. Many miRNA sequencing studies reveal that miRNA variations such as isomiRs and “arm switching” are biologically relevant. However, existing standalone tools usually do not provide comprehensive, detailed information on miRNA variations. To deepen our understanding of miRNA variability, we developed a new standalone tool called “mirPRo” to quantify known miRNAs and predict novel miRNAs. Compared with the most widely used standalone program, miRDeep2, mirPRo offers several new functions including read cataloging based on genome annotation, optional seed region check, miRNA family expression quantification, isomiR identification and categorization and “arm switching” detection. Our comparative data analyses using three datasets from mouse, human and chicken demonstrate that mirPRo is more accurate than miRDeep2 by avoiding over-counting of sequence reads and by implementing different approaches in adapter trimming, mapping and quantification. mirPRo is an open-source standalone program (https://sourceforge.net/projects/mirpro/).

International audience; Evaluating the strong scalability of OpenMP applications is a costly and time-consuming process. It traditionally requires executing the whole application multiple times with different number of threads. We propose the Parallel Codelet Extractor and REplayer (PCERE), a tool to reduce the cost of scalability evaluation. PCERE decomposes applications into small pieces called codelets: each codelet maps to an OpenMP parallel region and can be replayed as a standalone program. To accelerate scalability prediction, PCERE replays codelets while varying the number of threads. Prediction speedup comes from two key ideas. First, the number of invocations during replay can be significantly reduced. Invocations that have the same performance are grouped together and a single representative is replayed. Second, sequential parts of the programs do not need to be replayed for each different thread configuration. PCERE codelets can be captured once and replayed accurately on multiple architectures, enabling cross-architecture parallel performance prediction. We evaluate PCERE on a C version of the NAS 3.0 Parallel Benchmarks (NPB). We achieve an average speed-up of 25 times on evaluating OpenMP applications scalability with an average error of 4.9\% (median error of 1.7\%).

The single-pass (continuous) program is the basis of the feed-and-bleed program and the batch program. This is because the single-pass program describes the function of the electrodialyzer. This chapter describes the stand-alone single-pass program established based on the principles of electrochemistry and electrodialysis experiments being supplied strong electrolyte solutions. Calculation is carried out in the spreadsheet with the use of common software (Excel) and ordinary hardware (computer). The program is integrated in Web sites. So, readers can operate the program in the websites by inputting the source code, i.e., optional process specifications and operating conditions. The program aims to function as a pilot plant operation. The single-pass program is classified to (1) Constant current program, (2) constant voltage program, and (3) constant salt concentration program. The process specifications and electrodialysis conditions are inputted into the programs and the performance of the processes are computed with trial-and-error calculations.

A complete system for the implementation of digital logic in a fine-grain reconfigurable platform is introduced. The system is composed of two parts. The fine-grain reconfigurable hardware platform (FPGA) on which the logic is implemented and the set of CAD tools for mapping logic to the FPGA platform. A novel energy-efficient FPGA architecture is presented (CLB, interconnect network, configuration hardware) and simulated in STM 0.18 μm CMOS technology. Concerning the tool flow, each tool can operate as a standalone program as well as part of a complete design framework, composed by existing and new tools.

Many biologists are familiar with BLAST (Basic Local Alignment Search Tool). A major difficulty with BLAST is searching a massive number of queries without depending on professional help with scripting languages. Hence, we describe the development of an interface for BLAST to perform sequence search for a set of query sequences at one instance. This software interface runs on all Windows-based personal computers (PCs) and can be widely used by biologists who are not familiar with professional informatics command languages and yet want to perform massive sequence analysis. easySEARCH is freely available as a standalone program. Availability http://210.219.44.213/easysearch_down.html

This work designs, develops and implements a virtual laboratory for digital circuit design in Macro Universities that can create a rich learning environment for students from all over the world. Our system consists of four parts: agent execution environments, mobile agents, wrapper agents and experimental platforms. Mobile agents are received and executed in the agent execution environment, which provides locations and other resources for the mobile agents. The wrapper agent acts as a middleware for the mobile agent and the experimental platform. The experimental platform is an existing application program that could be a learning program, such as a CAI tool or a design tool, such as a CAD system. The major merit of our system is that it enables network capability for a standalone program without the need for the source code of the original program. The prototype of our virtual laboratory is targeted at a digital circuit laboratory. Experimental results demonstrate the feasibility of our approach.

Background The software available to date for analyzing image sequences from time-lapse microscopy works only for certain bacteria and under limited conditions. These programs, mostly MATLAB-based, fail for microbes with irregular shape, indistinct cell division sites, or that grow in closely packed microcolonies. Unfortunately, many organisms of interest have these characteristics, and analyzing their image sequences has been limited to time consuming manual processing. Results Here we describe BactImAS – a modular, multi-platform, open-source, Java-based software delivered both as a standalone program and as a plugin for Icy. The software is designed for extracting and visualizing quantitative data from bacterial time-lapse movies. BactImAS uses a semi-automated approach where the user defines initial cells, identifies cell division events, and, if necessary, manually corrects cell segmentation with the help of user-friendly GUI and incorporated ImageJ application. The program segments and tracks cells using a newly-developed algorithm designed for movies with difficult-to-segment cells that exhibit small frame-to-frame differences. Measurements are extracted from images in a configurable, automated fashion and an SQLite database is used to store, retrieve, and exchange all acquired data. Finally, the BactImAS can generate configurable lineage tree visualizations and export data as CSV files. We tested BactImAS on time-lapse movies of Mycobacterium smegmatis and achieved at least 10-fold reduction of processing time compared to manual analysis. We illustrate the power of the visualization tool by showing heterogeneity of both icl expression and cell growth atop of a lineage tree. Conclusions The presented software simplifies quantitative analysis of time-lapse movies overall and is currently the only available software for the analysis of mycobacteria-like cells. It will be of interest to the community of both end-users and developers of time-lapse microscopy software. Electronic supplementary material The online version of this article (doi:10.1186/1471-2105-15-251) contains supplementary material, which is available to authorized users.

We present a database client software-Neurovascular Network Explorer 1.0 (NNE 1.0)-that uses MATLAB® based Graphical User Interface (GUI) for interaction with a database of 2-photon single-vessel diameter measurements from our previous publication (Tian et al., 2010). These data are of particular interest for modeling the hemodynamic response. NNE 1.0 is downloaded by the user and then runs either as a MATLAB script or as a standalone program on a Windows platform. The GUI allows browsing the database according to parameters specified by the user, simple manipulation and visualization of the retrieved records (such as averaging and peak-normalization), and export of the results. Further, we provide NNE 1.0 source code. With this source code, the user can database their own experimental results, given the appropriate data structure and naming conventions, and thus share their data in a user-friendly format with other investigators. NNE 1.0 provides an example of seamless and low-cost solution for sharing of experimental data by a regular size neuroscience laboratory and may serve as a general template, facilitating dissemination of biological results and accelerating data-driven modeling approaches. © 2014 Sridhar, Tian, Dale, Devor and Saisan.

AvoPlot is a simple-to-use graphical plotting program written in Python and making extensive use of the matplotlib plotting library. It can be found at http://code.google.com/p/avoplot/. In addition to providing a user-friendly interface to the powerful capabilities of the matplotlib library, it also offers users the possibility of extending its functionality by creating plug-ins. These can import specific types of data into the interface and also provide new tools for manipulating them. In this respect, AvoPlot is a convenient platform for researchers to build their own data analysis tools on top of, as well as being a useful standalone program.

Background Understanding the relationship between the millions of functional DNA elements and their protein regulators, and how they work in conjunction to manifest diverse phenotypes, is key to advancing our understanding of the mammalian genome. Next-generation sequencing technology is now used widely to probe these protein-DNA interactions and to profile gene expression at a genome-wide scale. As the cost of DNA sequencing continues to fall, the interpretation of the ever increasing amount of data generated represents a considerable challenge. Results We have developed ngs.plot – a standalone program to visualize enrichment patterns of DNA-interacting proteins at functionally important regions based on next-generation sequencing data. We demonstrate that ngs.plot is not only efficient but also scalable. We use a few examples to demonstrate that ngs.plot is easy to use and yet very powerful to generate figures that are publication ready. Conclusions We conclude that ngs.plot is a useful tool to help fill the gap between massive datasets and genomic information in this era of big sequencing data.

This report provides a User s Guide to the Missile Design Tool (MDT). MDT is a standalone program that can preliminarily estimate several important performance parameters of a solid rocket using aerodynamic and motor information. This report explains the user interface and input at length as well as providing an in-depth explanation of the simulation output and its interpretation.

In this paper, it is presented the implementation of a solar-powered pumping system configurator based on a new approach for the modelling of the configuration process of product families. An important outcome of this approach is that if a few modelling conditions are satisfied, deriving product family members becomes a direct (backtrack-free) process. Consequently, a configuration problem-solving process that typically would require a high-performance computer can be squeezed into handheld devices as a standalone program.

PLUMED-GUI is an interactive environment to develop and test complex PLUMED scripts within the Visual Molecular Dynamics (VMD) environment. Computational biophysicists can take advantage of both PLUMED’s rich syntax to define collective variables (CVs) and VMD’s chemically-aware atom selection language, while working within a natural point-and-click interface. Pre-defined templates and syntax mnemonics facilitate the definition of well-known reaction coordinates. Complex CVs, e.g. involving reference snapshots used for RMSD or native contacts calculations, can be built through dialogs that provide a synoptic view of the available options. Scripts can be either exported for use in simulation programs, or evaluated on the currently loaded molecular trajectories. Script development takes place without leaving VMD, thus enabling an incremental try–see–modify development model for molecular metrics. Program summary Program title: PLUMED-GUI (Collective variable analysis plugin) Catalogue identifier: AERU_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AERU_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: 3-clause BSD Open Source No. of lines in distributed program, including test data, etc.: 2651 No. of bytes in distributed program, including test data, etc.: 32359 Distribution format: tar.gz Programming language: TCL/TK. Computer: Workstations, PCs. Operating system: Linux/Unix, OSX, Windows. RAM: Sufficient to run PLUMED [1] and VMD [2]. Classification: 3, 23. Subprograms used: Cat Id Title Reference AEEE_v2_0 PLUMED CPC 185 (2014) 604 Nature of problem: Compute and visualize values of collective variables on molecular dynamics trajectories from within VMD, and interactively develop biasing scripts for the estimation of free-energy surfaces in PLUMED. Solution method: A graphical user interface is integrated in VMD and allows the user to interactively develop and run analysis scripts. Menus and dialogs provide mnemonics and documentation on the syntax to define complex CVs. Restrictions: Tested on systems up to 100,000 atoms. Unusual features: VMD–PLUMED is not a standalone program but a plugin that provides access to PLUMED’s analysis features from within VMD. Additional comments: Distributed with VMD since version 1.9.0. Manual update may be required to access the latest features. Running time: Computations of the values of collective variables, performed by the underlying PLUMED code, depends on the size of the system and the length of the trajectory; it is generally negligible with respect to simulation time. References: [1] G. A. Tribello, M. Bonomi, D. Branduardi, C. Camilloni, G. Bussi, PLUMED 2: New feathers for an old bird, Computer Physics Communications 185 (2014) 604. [2] W. Humphrey, A. Dalke, K. Schulten, VMD: visual molecular dynamics, J Mol Graph 14 (1996) 33–38.

Maple is a computer algebra system that has the potential to be the tool of choice for many computational problems in science and engineering. In this article, we show how Maple can be used to develop graphical images of thermodynamic functions. We also describe ThermoView, a standalone program that can display Maple-based images and animations. The visual images and tools described here can be used to enhance thermodynamics courses and give students an improved perspective on the relationships between thermodynamic state variables. © 1999 John Wiley & Sons, Inc. Comput Appl Eng Educ 6: 223–234, 1998

Molecular dynamics simulations have a prominent role in biophysics and drug discovery due to the atomistic information they provide on the structure, energetics and dynamics of biomolecules. Specialized software packages are required to analyze simulated trajectories, either interactively or via scripts, to derive quantities of interest and provide insight for further experiments. This paper presents the Density Profile Tool, a package that enhances the Visual Molecular Dynamics environment with the ability to interactively compute and visualize 1-D projections of various density functions of molecular models. We describe how the plugin is used to perform computations both via a graphical interface and programmatically. Results are presented for realistic examples, all-atom bilayer models, showing how mass and electron densities readily provide measurements such as membrane thickness, location of structural elements, and how they compare to X-ray diffraction experiments. Program summary Program title: Density Profile Tool Catalogue identifier: AEQM_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEQM_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: yes No. of lines in distributed program, including test data, etc.: 1742 No. of bytes in distributed program, including test data, etc.: 12764 Distribution format: tar.gz Programming language: TCL/TK. Computer: Any, with or without graphical display. Operating system: Linux/Unix, OSX, Windows. RAM: VMD should be able to hold the trajectory in memory. Classification: 3, 23. External routines: VMD (version 1.9 or higher) ( http://www.ks.uiuc.edu/Research/vmd/ ). Nature of problem: Compute and visualize one-dimensional density profiles of molecular dynamics trajectories in the VMD environment, either interactively or programmatically. Solution method: Density profiles are computed by binning the simulation space into slabs of finite thickness. A graphical user interface allows the choice of the atomic property (number, mass, charge, electrons) and the details of the binning. Restrictions: The current version only supports orthorhombic cells. Unusual features: The Density Profile Tool is not a standalone program but a plug-in that enhances VMD’s analysis features. Running time: A contemporary PC completes the analysis of 500 frames of the example system discussed in the paper (35,000 atoms) in under 1 min.

pyGeno is a Python package mainly intended for precision medicine applications that revolve around genomics and proteomics. It integrates reference sequences and annotations from Ensembl, genomic polymorphisms from the dbSNP database and data from next-gen sequencing into an easy to use, memory-efficient and fast framework, therefore allowing the user to easily explore subject-specific genomes and proteomes. Compared to a standaloneprogram, pyGeno gives the user access to the complete expressivity of Python, a general programming language. Its range of application therefore encompasses both short scripts and large scale genome-wide studies.

Many biological processes are performed by a group of proteins rather than by individual proteins. Proteins involved in the same biological process often form a densely connected sub-graph in a protein-protein interaction network. Therefore, finding a dense sub-graph provides useful information to predict the function or protein complex of uncharacterised proteins in the sub-graph. We developed a heuristic algorithm that finds functional modules in a protein-protein interaction network and visualises the modules. The algorithm has been implemented in a platform-independent, standalone program called ModuleSearch. In an interaction network of yeast proteins, ModuleSearch found 366 overlapping modules. Of the modules, 71% have a function shared by more than half the proteins in the module and 58% have a function shared by all proteins in the module. Comparison of ModuleSearch with other programs shows that ModuleSearch finds more sub-graphs than most other programs, yet a higher proportion of the sub-graphs correspond to known functional modules. ModuleSearch and sample data are freely available to academics at http://bclab.inha.ac.kr/ModuleSearch.

Summary: The diverse functional roles of non-coding RNA molecules are determined by their underlying structure. ModeRNA server is an online tool for RNA 3D structure modeling by the comparative approach, based on a template RNA structure and a user-defined target-template sequence alignment. It offers an option to search for potential templates, given the target sequence. The server also provides tools for analyzing, editing and formatting of RNA structure files. It facilitates the use of the ModeRNA software and offers new options in comparison to the standalone program. Availability and implementation: ModeRNA server was implemented using the Python language and the Django web framework. It is freely available at http://iimcb.genesilico.pl/modernaserver. Contact: iamb@genesilico.pl