User-friendly Program Research Articles

GAFit: A general-purpose, user-friendly program for fitting potential energy surfaces

We have developed a software package based on a genetic algorithm that fits an analytic function to a given set of data points. The code, called GAFit, was also interfaced with the CHARMM and MOPAC programs in order to facilitate force field parameterizations and fittings of specific reaction parameters (SRP) for semiempirical Hamiltonians. The present tool may be applied to a wide range of fitting problems, though it has been especially designed to significantly reduce the hard work involved in the development of potential energy surfaces for complex systems. For this purpose, it has been equipped with several programs to help the user in the preparation of the input files. We showcase the application of the computational tool to several chemical-relevant problems: force-field parameterization, with emphasis on nonbonded energy terms or intermolecular potentials, derivation of SRP for semiempirical Hamiltonians, and fittings of generic analytical functions. Program summaryProgram title : GAFitProgram Files doi : http://dx.doi.org/10.17632/9gy6bjcwk5.1Licensing provisions : GNU General Public License 3 (GPL)Programming language : Fortran 90, C, Perl and JavaNature of problem : Potential energy surfaces (PESs) have a key role in reaction dynamics and molecular dynamics. Chemical dynamics simulations can be performed by using analytical PESs or by direct dynamics, that is, by computing energies and forces “on-the-fly” by molecular structure calculations. The development of analytical PESs is, quite often, a very complex and tedious task. There are several programs in the literature that may help to develop PESs but, as far as we know, none of them show, at the same time, great generality and flexibility.Solution method : GAFit was designed to help users develop analytical potential energy functions. We made special efforts to write a code that exhibits the three features mentioned above. For this reason, we have also interfaced GAFit with the CHARMM and MOPAC programs. The former is one of the popular packages for molecular dynamics and the latter is a semiempirical quantum chemistry program that may be conveniently used for direct dynamics simulations. Because, in general, the fitting of PESs involves a simultaneous optimization of many nonlinear parameters, we have selected a genetic algorithm as the driver for the parameterizations. As shown in the paper, GAFit may be applied to other fitting problems.

SOFIA: An R Package for Enhancing Genetic Visualization With Circos

Visualization of data from any stage of genetic and genomic research is one of the most useful approaches for detecting potential errors, ensuring accuracy and reproducibility, and presentation of the resulting data. Currently software such as Circos, ClicO FS, and RCircos, among others, provide tools for plotting a variety of genetic data types in a concise manner for data exploration and presentation. However, each of the programs has 1 or more disadvantages that limit their usability in data exploration or construction of publication quality figures, such as inflexibility in formatting and configuration, reduced image quality, lack of potential for automation, or requirements of high-level computational expertise. Therefore, we developed the R package SOFIA, which leverages the capabilities of Circos by manipulating data, preparing configuration files, and running the Perl-native Circos directly from the R environment with minimal user intervention. The advantages of integrating both R and Circos into SOFIA are numerous. R is a very powerful and user-friendly programming language widely used among the genetic and genomic research community, while Circos has proven to be a novel software for arranging genomic data to create aesthetical publication quality circular figures. Producing Circos figures in R with SOFIA is simple, requires minimal coding experience, even for complex figures that incorporate high-dimensional genetic information, and allows simultaneous analysis and visual exploration of genomic and genetic data in a single programming environment.

RMATS-DVR: rMATS discovery of differential variants in RNA.

RNA sequences of a gene can have single nucleotide variants (SNVs) due to single nucleotide polymorphisms (SNPs) in the genome, or RNA editing events within the RNA. By comparing RNA-seq data of a given cell type before and after a specific perturbation, we can detect and quantify SNVs in the RNA and discover SNVs with altered frequencies between distinct cellular states. Such differential variants in RNA (DVRs) may reflect allele-specific changes in gene expression or RNA processing, as well as changes in RNA editing in response to cellular perturbations or stimuli. We have developed rMATS-DVR, a convenient and user-friendly software program to streamline the discovery of DVRs between two RNA-seq sample groups with replicates. rMATS-DVR combines a stringent GATK-based pipeline for calling SNVs including SNPs and RNA editing events in RNA-seq reads, with our rigorous rMATS statistical model for identifying differential isoform ratios using RNA-seq sequence count data with replicates. We applied rMATS-DVR to RNA-seq data of the human chronic myeloid leukemia cell line K562 in response to shRNA knockdown of the RNA editing enzyme ADAR1. rMATS-DVR discovered 1372 significant DVRs between knockdown and control. These DVRs encompassed known SNPs and RNA editing sites as well as novel SNVs, with the majority of DVRs corresponding to known RNA editing sites repressed after ADAR1 knockdown. rMATS-DVR is at https://github.com/Xinglab/rMATS-DVR . yxing@ucla.edu. Supplementary data are available at Bioinformatics online.

ORBIT: A Platform for Smartphone-Based Data-Intensive Sensing Applications

Owing to the rich processing, multi-modal sensing, and versatile networking capabilities, smartphones are increasingly used to build data-intensive embedded sensing applications. However, various challenges must be systematically addressed before smartphones can be used as a generic embedded sensing platform, including high power consumption, lack of real-time functionality, and user-friendly embedded programming support. This paper presents ORBIT, a smartphone-based platform for data-intensive embedded sensing applications. ORBIT features a tiered architecture, in which a smartphone can interface to an energy-efficient peripheral board and/or a cloud service. ORBIT as a platform addresses the shortcomings of current smartphones while utilizing their strengths. ORBIT provides a profile-based task partitioning that allows it to intelligently dispatch the processing tasks among the tiers to minimize the system power consumption. ORBIT also provides a data processing library that includes two mechanisms namely adaptive delay-quality trade-off and data partitioning via multi-threading to optimize resource usage. Moreover, ORBIT supplies an annotation-based programming API for developers that significantly simplifies the application development and provides programming flexibility. Extensive microbenchmark evaluation and three case studies including seismic sensing, visual tracking using an ORBIT robot, and multi-camera 3D reconstruction, validate the generic design of ORBIT.

DLPlib: A Library for Deep Learning Processor

Recently, deep learning processors have become one of the most promising solutions of accelerating deep learning algorithms. Currently, the only method of programming the deep learning processors is through writing assembly instructions by bare hands, which costs a lot of programming efforts and causes very low efficiency. One solution is to integrate the deep learning processors as a new back-end into one prevalent high-level deep learning framework (e.g., TPU (tensor processing unit) is integrated into Tensorflow directly). However, this will obstruct other frameworks to profit from the programming interface. The alternative approach is to design a framework-independent low-level library for deep learning processors (e.g., the deep learning library for GPU, cuDNN). In this fashion, the library could be conveniently invoked in high-level programming frameworks and provides more generality. In order to allow more deep learning frameworks to gain benefits from this environment, we envision it as a low-level library which could be easily embedded into current high-level frameworks and provide high performance. Three major issues of designing such a library are discussed. The first one is the design of data structures. Data structures should be as few as possible while being able to support all possible operations. This will allow us to optimize the data structures easier without compromising the generality. The second one is the selection of operations, which should provide a rather wide range of operations to support various types of networks with high efficiency. The third is the design of the API, which should provide a flexible and user-friendly programming model and should be easy to be embedded into existing deep learning frameworks. Considering all the above issues, we propose DLPlib, a tensor-filter based library designed specific for deep learning processors. It contains two major data structures, tensor and filter, and a set of operators including basic neural network primitives and matrix/vector operations. It provides a descriptor-based API exposed as a C++ interface. The library achieves a speedup of 0.79x compared with the performance of hand-written assembly instructions.

CryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination.

Single-particle electron cryomicroscopy (cryo-EM) is a powerful method for determining the structures of biological macromolecules. With automated microscopes, cryo-EM data can often be obtained in a few days. However, processing cryo-EM image data to reveal heterogeneity in the protein structure and to refine 3D maps to high resolution frequently becomes a severe bottleneck, requiring expert intervention, prior structural knowledge, and weeks of calculations on expensive computer clusters. Here we show that stochastic gradient descent (SGD) and branch-and-bound maximum likelihood optimization algorithms permit the major steps in cryo-EM structure determination to be performed in hours or minutes on an inexpensive desktop computer. Furthermore, SGD with Bayesian marginalization allows ab initio 3D classification, enabling automated analysis and discovery of unexpected structures without bias from a reference map. These algorithms are combined in a user-friendly computer program named cryoSPARC (http://www.cryosparc.com).

Simulating Electron Paramagnetic Resonance Spectra of Slow-Motion Systems in the Time Domain

Electron paramagnetic resonance (EPR) spectroscopy has proven to be an excellent tool for probing local structure and dynamics in biological systems. However, the corresponding spectra can be complex and difficult to interpret. In order to accurately interpret experimental data, there has been a corresponding active development of computational tools and user-friendly programs to simulate continuous-wave (CW) EPR spectra, especially those in the slow-motion regime (dynamical time scales of ≈10-100 ns for nitroxides at 9-10 GHz). Though the standard method has been to numerically solve the stochastic Liouville equation in the frequency domain, more recently, simulating CW EPR spectra in the time domain has become increasingly popular. Existing works have applied this method by simulating spin relaxation due to rotational diffusion, either by generating stochastic or molecular dynamics trajectories. Other significant spin relaxation mechanisms that affect CW EPR spectral lineshapes have been treated in a phenomenological manner. In order to bridge this gap in computational complexity and more accurately simulate EPR spectra obtained in experiments, we extend previous treatments by explicitly including other spin relaxation mechanisms and explore additional motional models. In addition, our programs are implemented in the widely used Matlab software environment.

Making Classical and Hybrid (QM/MM) Molecular Dynamics Easy and Fast with QwikMD

“Everything that living things do can be understood in terms of jigglings and wigglings of atoms.” Richard Feynman's remarks in the early 1960's summarize what is today widely accepted, namely, that molecular processes can be described by the dynamics of biological molecules, therefore connecting protein function with protein dynamics. Molecular dynamics (MD) simulation, in this regard, is the major methodology employed in structural biology to explore the dynamical behavior of macromolecules. Although the use of MD simulations has consistently increased over the last decades, the barrier imposed by the initial learning curve of the MD packages is still high. To assist new users in overcoming this barrier, and to help the more advanced users to speed up tedious preparation steps, we developed QwikMD(1). This user-friendly program connects the widely used molecular graphics program VMD to the widely adopted MD program NAMD. Employing QwikMD, a user is able to setup an MD simulation in just a few minutes, allowing quick studies of point mutations, partial deletions or even atomic force microscopy experiments. Within the different modules of QwikMD, one can adopt a myriad of simulation protocols, from single protein in vacuum to hybrid QM/MM simulations. QwikMD makes it easy for a new user to perform MD simulations, while it also serves as a learning tool. Many “info buttons” provide the theoretical background underlying the MD procedures carried out in modern MD simulations.1. J. V Ribeiro et al., QwikMD — Integrative Molecular Dynamics Toolkit for Novices and Experts. Sci. Rep. 6, 26536 (2016).

Three-dimensional image reconstruction with free open-source OsiriX software in video-assisted thoracoscopic lobectomy and segmentectomy

ObjectiveThe aim of this retrospective study was to evaluate the practice and the feasibility of Osirix, a free and open-source medical imaging software, in performing accurate video-assisted thoracoscopic lobectomy and segmentectomy. MethodsFrom July 2014 to April 2016, 63 patients received anatomical video-assisted thoracoscopic surgery (VATS), either lobectomy or segmentectomy, in our department. Three-dimensional (3D) reconstruction images of 61 (96.8%) patients were preoperatively obtained with contrast-enhanced computed tomography (CT).Preoperative resection simulations were accomplished with patient-individual reconstructed 3D images. For lobectomy, pulmonary lobar veins, arteries and bronchi were identified meticulously by carefully reviewing the 3D images on the display. For segmentectomy, the intrasegmental veins in the affected segment for division and the intersegmental veins to be preserved were identified on the 3D images. Patient preoperative characteristics, surgical outcomes and postoperative data were reviewed from a prospective database. ResultsThe study cohort of 63 patients included 33 (52.4%) men and 30 (47.6%) women, of whom 46 (73.0%) underwent VATS lobectomy and 17 (27.0%) underwent VATS segmentectomy. There was 1 conversion from VATS lobectomy to open thoracotomy because of fibrocalcified lymph nodes. A VATS lobectomy was performed in 1 case after completing the segmentectomy because invasive adenocarcinoma was detected by intraoperative frozen-section analysis. There were no 30-day or 90-day operative mortalities ConclusionsThe free, simple, and user-friendly software program Osirix can provide a 3D anatomic structure of pulmonary vessels and a clear vision into the space between the lesion and adjacent tissues, which allows surgeons to make preoperative simulations and improve the accuracy and safety of actual surgery.

A New Look at Kinetics in Relation to Food Storage.

Modern mathematical software and user-friendly interactive programs can simplify and speed up kinetics calculations. They also open the way for new approaches to storage data gathering and analysis. This is demonstrated with a recently introduced simple exponential model that is interchangeable with the Arrhenius equation and endpoints and successive points methods and that estimates chemical degradation kinetics parameters from a small number of isothermal or nonisothermal experimental data. Also presented are a method to determine shelf life using two chemical markers and a global phenomenological model for peaked reactions, such as those encountered in lipid oxidation. Also recently introduced are freely downloadable Wolfram Demonstrations and other interactive software to generate, visualize, examine, and/or compare actual or hypothetical storage scenarios in minutes. They include programs that solve pairs of simultaneous nonlinear algebraic or differential rate equations by passing two reconstructed degradation curves, or a single nonisothermal curve, through two entered experimental points by moving the degradation parameters' sliders on the screen.

Optimal Design for Conventional Wastewater Treatment Systems using a Computing Language MATLAB R2012a

In the present scenario of rapid urbanization, the demand for wastewater treatment is continuously increasing. The majority of research in the field of wastewater treatment plant (WWTP) is focusing on its modeling part. The design of WWTP is developed using professional quality software packages which incorporate the fundamental concepts with the key engineering principles. With the aim to obtain an optimal design, in this study a novel Decision Support System (DSS) is developed for the preliminary units integrating screening chamber, grit chamber and equalization tank with primary sedimentation tank as the primary process and activated sludge process, trickling filter and rotating biological contactor as different types of the secondary units of Wastewater Treatment System using a computing language MATLAB R2012a. DSS is a comprehensive and user-friendly program which could incorporate most of the theoretical and practical constraints. One of the major concerns of DSS is the dimension constraint for the design and operation of WWTP. DSS incorporates miscellaneous mathematical functions and the code to develop a user-desired design. The applicability of the DSS model is illustrated through the various design problems. The design developed will support the future growth and development of the cost optimization models for WWTP.

RNA Secondary Structure Prediction.

In this unit, protocols are provided for predicting RNA secondary structure with the user-friendly RNAstructure desktop computer program and the RNAstructure Web server. The minimum free energy structure and a set of suboptimal structures with similar free energies are predicted. Prediction of high-affinity oligonucleotide binding sites to a structured RNA target is also presented. © 2016 by John Wiley & Sons, Inc.

A multi-agent systems-based contractor pre-qualification model

Purpose The selection of the contractor, as a main participant of a construction project, is the most important and challenging decision process for a client. The purpose of this paper is to propose a multi-agent systems (MAS)-based contractor pre-qualification (CP) model for the construction sector in the frame of the tender management system. Design/methodology/approach The meta-classification and analysis study of the existing literature on CP, contractor selection and criteria weighting issues, which examines the current and important CP criteria, other than price, is introduced structurally. A quantitative survey, which is carried out to estimate initial weightings of the identified criteria, is overviewed. MAS are used to model the pre-qualification process and workflows are shown in Petri nets formalism. A user-friendly prototype program is created in order to simulate the tendering process. In addition, a real case regarding the construction work in Turkey is analyzed. Findings There is a lack of non-human-driven solutions and automation in CP and in the selection problem. The proposed model simulates the pre-qualification process and provides consistent results. Research limitations/implications The meta-classification study consists of only peer-reviewed papers between 1992 and 2013 and the quantitative survey initiates the perspectives of the actors of Turkish construction sector. Only the traditional project delivery method is selected for the proposed model, that is other delivery methods such as design/build, project management, etc., are not considered. Open, selective limited and negotiated tendering processes are examined in the study and the direct supply is not considered in the scope. Practical implications The implications will help to provide an objective CP and selection process and to prevent the delays, costs and other troubles, which are caused by the false selection of a contractor. Originality/value Automation and simulation in the pre-qualification and the selection of the contractor with a non-human-driven intelligent solution ease the decision processes of clients in terms of cost, time and quality.

Just Another Gibbs Sampler (JAGS)

A review of the software Just Another Gibbs Sampler (JAGS) is provided. We cover aspects related to history and development and the elements a user needs to know to get started with the program, including (a) definition of the data, (b) definition of the model, (c) compilation of the model, and (d) initialization of the model. An example using a latent class model with large-scale education data is provided to illustrate how easily JAGS can be implemented in R. We also cover details surrounding the many programs implementing JAGS. We conclude with a discussion of the newest features and upcoming developments. JAGS is constantly evolving and is developing into a flexible, user-friendly program with many benefits for Bayesian inference.

Cif2tube – Algorithm for constructing nanotube and nanoscroll models from crystallographic information files

This study developed a user-friendly program, cif2tube, to facilitate the construction of a nanotube or a nanoscroll model using an input crystallographic information file (*.cif file). This program makes it possible for users to determine several parameters used in the construction of the nanotube/nanoscroll model, including the chirality, the directions in which it will roll-up, and the interlayer spacing of the nanoscroll. The ability to vary these parameters enables the customization of the resulting models. The capability of the cif2tube program was demonstrated by constructing models of existing as well as hypothetical nanotube/nanoscroll materials. The as-generated models from cif2tube were then compared with models obtained from commercial molecular simulation packages and as-generated models that were subjected to geometric optimization and molecular dynamics simulations. We also demonstrated the capability of cif2tube in the creation of models comprising hypothetical nanotubes of perovskite, zeolite, and metal organic frameworks (MOFs). cif2tube enables the creation of a large variety of existing and novel nanotube models to facilitate the computational study of nanotube materials.

Computer-Controlled Eucapnic Voluntary Hyperpnea Challenge Method

Eucapnic voluntary hyperpnea (EVH) challenge is a well-established and sensitive method of determining the degree of bronchoconstriction at hospitals and clinics. This paper presents the development of a computer-controlled system for assessing exercise-induced bronchoconstriction (EIB) in humans including a computer graphic user interface (GUI) to control a low-pressure demand valve for better efficiency. GUI is designed to monitor the severity of acute lung airway narrowing using a matlab software and to present the measurement data into a simple user-friendly program consisting of patient information, EVH test analysis, and detection of exercise-induced asthma (EIA) and EIB. The proposed system is assessed using human subjects. Typical outputs from this system showed that for a female participant, a 20.25% and a 15.61% decrease from baseline in her forced expiratory volume in 1 s (FEVl) after 10 and 15 min of the challenge commencement, respectively. Her actual expiratory flow rate (45.833 L/m) and actual total volume of gas respired (275 L) were smaller than the target values. This system widens the usage of EVH challenge in medical areas, and the GUI may serve as a new clinical computer-aided diagnostic tool to help healthcare professionals noninvasively monitor the severity of asthma, EIA, and EIB.

One-Tube-Only Standardized Site-Directed Mutagenesis: An Alternative Approach to Generate Amino Acid Substitution Collections.

Site-directed mutagenesis (SDM) is a powerful tool to create defined collections of protein variants for experimental and clinical purposes, but effectiveness is compromised when a large number of mutations is required. We present here a one-tube-only standardized SDM approach that generates comprehensive collections of amino acid substitution variants, including scanning- and single site-multiple mutations. The approach combines unified mutagenic primer design with the mixing of multiple distinct primer pairs and/or plasmid templates to increase the yield of a single inverse-PCR mutagenesis reaction. Also, a user-friendly program for automatic design of standardized primers for Ala-scanning mutagenesis is made available. Experimental results were compared with a modeling approach together with stochastic simulation data. For single site-multiple mutagenesis purposes and for simultaneous mutagenesis in different plasmid backgrounds, combination of primer sets and/or plasmid templates in a single reaction tube yielded the distinct mutations in a stochastic fashion. For scanning mutagenesis, we found that a combination of overlapping primer sets in a single PCR reaction allowed the yield of different individual mutations, although this yield did not necessarily follow a stochastic trend. Double mutants were generated when the overlap of primer pairs was below 60%. Our results illustrate that one-tube-only SDM effectively reduces the number of reactions required in large-scale mutagenesis strategies, facilitating the generation of comprehensive collections of protein variants suitable for functional analysis.

LncRNATargets: A platform for lncRNA target prediction based on nucleic acid thermodynamics.

Many studies have supported that long noncoding RNAs (lncRNAs) perform various functions in various critical biological processes. Advanced experimental and computational technologies allow access to more information on lncRNAs. Determining the functions and action mechanisms of these RNAs on a large scale is urgently needed. We provided lncRNATargets, which is a web-based platform for lncRNA target prediction based on nucleic acid thermodynamics. The nearest-neighbor (NN) model was used to calculate binging-free energy. The main principle of NN model for nucleic acid assumes that identity and orientation of neighbor base pairs determine stability of a given base pair. lncRNATargets features the following options: setting of a specific temperature that allow use not only for human but also for other animals or plants; processing all lncRNAs in high throughput without RNA size limitation that is superior to any other existing tool; and web-based, user-friendly interface, and colored result displays that allow easy access for nonskilled computer operators and provide better understanding of results. This technique could provide accurate calculation on the binding-free energy of lncRNA-target dimers to predict if these structures are well targeted together. lncRNATargets provides high accuracy calculations, and this user-friendly program is available for free at http://www.herbbol.org:8001/lrt/ .

Framework to parameterize and validate APEX to support deployment of the nutrient tracking tool

The Agricultural Policy Environmental eXtender (APEX) model is the scientific basis for the Nutrient Tracking Tool (NTT). NTT is an enhanced version of the Nitrogen Trading Tool, a user-friendly web-based computer program originally developed by the USDA. NTT was developed to estimate reductions in nutrient losses to the environment associated with alternative practices. The relatively easy access and ease with which the interface can be used has provided opportunities to demonstrate NTT in locations throughout the country; however, the absence of a clearly defined, consistent approach to parameterization and validation has raised questions over the reliability and consistency of simulated results. In this study: guidelines for parameterization and validation of APEX were developed based on literature review findings and the authors’ experience; and a case study was provided to illustrate how the developed guidelines are applied. The developed guidelines are in the form of recommendations covering essential phases of model simulation studies as well as a clear interpretation of model performance evaluation criteria thresholds and model simulation performance results. These guidelines were successfully applied in the central Ohio case study. The most sensitive water yield parameters and their respective reasonable range of values were determined. Simulated monthly and annual water yield values were within 5% and 15% of observed values during the calibration and validation periods, respectively. Overall, the developed guidelines together with the illustrative case study example are intended to serve as the framework to parameterize and validate APEX to support nation-wide deployment of NTT. This framework can be easily modified and used in additional APEX and other modeling studies.

Bayesian accrual prediction for interim review of clinical studies: open source R package and smartphone application.

BackgroundSubject recruitment for medical research is challenging. Slow patient accrual leads to increased costs and delays in treatment advances. Researchers need reliable tools to manage and predict the accrual rate. The previously developed Bayesian method integrates researchers’ experience on former trials and data from an ongoing study, providing a reliable prediction of accrual rate for clinical studies.MethodsIn this paper, we present a user-friendly graphical user interface program developed in R. A closed-form solution for the total subjects that can be recruited within a fixed time is derived. We also present a built-in Android system using Java for web browsers and mobile devices.ResultsUsing the accrual software, we re-evaluated the Veteran Affairs Cooperative Studies Program 558— ROBOTICS study. The application of the software in monitoring and management of recruitment is illustrated for different stages of the trial.ConclusionsThis developed accrual software provides a more convenient platform for estimation and prediction of the accrual process.Electronic supplementary materialThe online version of this article (doi:10.1186/s13063-016-1457-3) contains supplementary material, which is available to authorized users.