Showing papers on "Graphical user interface published in 2022"

FSLAM: A QGIS plugin for fast regional susceptibility assessment of rainfall-induced landslides

Abstract: Shallow slope failures triggered by rainfall commonly pose considerable risks in mountainous areas. In order to delineate areas where landslides are more prone to occur within a region, we have designed and developed a Python QGIS plugin named Fast Shallow Landslide Assessment Model (FSLAM). The plugin integrates a simplified hydrological model and a geotechnical model based on the infinite slope theory and contains two principal modules: runoff and slope stability modelling. It can output up to 15 raster maps describing the hydrological and stability conditions in a short computational time. Firstly, we explain the design of graphical user interface and the elements of the plugin. Then, the Berguedà area in NE Spain is used as case study to present the procedure of the plugin application. The results show that the accuracy of landslide susceptibility assessment performed by FSLAM-plugin is high and the computing time is only a few minutes. • A Python QGIS plugin is developed to simulate regional landslide susceptibility. • We explain the design of graphical user interface and the elements of the plugin. • 15 raster maps and 6 text files are outputs regarding hydrology and stability. • Plugin application and test by using landslide inventory in Berguedà (NE Spain).

ReciPro: free and open-source multipurpose crystallographic software integrating a crystal model database and viewer, diffraction and microscopy simulators, and diffraction data analysis tools

Abstract: ReciPro is a comprehensive multipurpose crystallographic program equipped with an intuitive graphical user interface (GUI), and it is completely free and open source. This software has a built-in crystal database consisting of over 20 000 crystal models, and the visualization system can seamlessly display a specified crystal model as an attractive three-dimensional graphic. The comprehensive features are not confined to these crystal model databases and viewers. It can smoothly and quantitatively simulate not only single-crystal and/or polycrystalline (powder) diffraction patterns of X-ray, electron and neutron diffraction of a selected crystal model, based on the kinematic scattering theory, but also various electron diffraction patterns and high-resolution transmission electron microscopy (TEM) images, based on the dynamical scattering theory. The features of stereographic projection of crystal planes/axes to explore crystal orientation relationships and the semi-automatic diffraction spot indexing function for experimental diffraction patterns assist diffraction experiments and analyses. These features are linked through a user-friendly GUI, and the results can be synchronously displayed almost in real time. ReciPro will assist a wide range of crystallographers (including beginners) using X-ray, electron and neutron diffraction crystallography and TEM.

AlphaPulldown—a python package for protein–protein interaction screens using AlphaFold-Multimer

Abstract: Summary The Artificial Intelligence-based structure prediction program AlphaFold-Multimer enabled structural modelling of protein complexes with unprecedented accuracy. Increasingly, AlphaFold-Multimer is also used to discover new protein-protein interactions. Here, we present AlphaPulldown, a Python package that streamlines protein-protein interaction screens and high-throughput modelling of higher-order oligomers using AlphaFold-Multimer. It provides a convenient command line interface, a variety of confidence scores, and a graphical analysis tool. Availability and implementation AlphaPulldown is freely available at https://www.embl-hamburg.de/AlphaPulldown.

AlphaPulldown—a python package for protein–protein interaction screens using AlphaFold-Multimer

Abstract: The artificial intelligence-based structure prediction program AlphaFold-Multimer enabled structural modelling of protein complexes with unprecedented accuracy. Increasingly, AlphaFold-Multimer is also used to discover new protein-protein interactions (PPIs). Here, we present AlphaPulldown, a Python package that streamlines PPI screens and high-throughput modelling of higher-order oligomers using AlphaFold-Multimer. It provides a convenient command-line interface, a variety of confidence scores and a graphical analysis tool.AlphaPulldown is freely available at https://www.embl-hamburg.de/AlphaPulldown.Supplementary note is available at Bioinformatics online.

iFeatureOmega: an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets

Abstract: Abstract The rapid accumulation of molecular data motivates development of innovative approaches to computationally characterize sequences, structures and functions of biological and chemical molecules in an efficient, accessible and accurate manner. Notwithstanding several computational tools that characterize protein or nucleic acids data, there are no one-stop computational toolkits that comprehensively characterize a wide range of biomolecules. We address this vital need by developing a holistic platform that generates features from sequence and structural data for a diverse collection of molecule types. Our freely available and easy-to-use iFeatureOmega platform generates, analyzes and visualizes 189 representations for biological sequences, structures and ligands. To the best of our knowledge, iFeatureOmega provides the largest scope when directly compared to the current solutions, in terms of the number of feature extraction and analysis approaches and coverage of different molecules. We release three versions of iFeatureOmega including a webserver, command line interface and graphical interface to satisfy needs of experienced bioinformaticians and less computer-savvy biologists and biochemists. With the assistance of iFeatureOmega, users can encode their molecular data into representations that facilitate construction of predictive models and analytical studies. We highlight benefits of iFeatureOmega based on three research applications, demonstrating how it can be used to accelerate and streamline research in bioinformatics, computational biology, and cheminformatics areas. The iFeatureOmega webserver is freely available at http://ifeatureomega.erc.monash.edu and the standalone versions can be downloaded from https://github.com/Superzchen/iFeatureOmega-GUI/ and https://github.com/Superzchen/iFeatureOmega-CLI/.

Berkeley Madonna Version 10–A simulation package for solving mathematical models

Abstract: Berkeley Madonna is a software program that provides an easy and intuitive environment for graphically building and numerically solving mathematical equations. Our users range from college undergraduates with little or no mathematical experience to academic researchers and professionals building and simulating sophisticated mathematical models that represent complex systems in the biological, chemical, and engineering fields. Here we briefly describe our recent advances including a new Java‐based user interface introduced in Version 9 and our transition from a 32‐ to 64‐bit architecture with the release of Version 10. We take the reader through an example tutorial that illustrates how to construct a mathematical model in Berkeley Madonna while highlighting some of the recent changes to the software. Specifically, we construct a standard pharmacokinetic model of the antifungal medication amphotericin B taken from the literature and discuss aspects related to model building, key numerical considerations, data fitting, and graphical visualization. We end by discussing planned functionality and features intended for future releases.

merlin, an improved framework for the reconstruction of high-quality genome-scale metabolic models

Abstract: Abstract Genome-scale metabolic models have been recognised as useful tools for better understanding living organisms’ metabolism. merlin (https://www.merlin-sysbio.org/) is an open-source and user-friendly resource that hastens the models’ reconstruction process, conjugating manual and automatic procedures, while leveraging the user's expertise with a curation-oriented graphical interface. An updated and redesigned version of merlin is herein presented. Since 2015, several features have been implemented in merlin, along with deep changes in the software architecture, operational flow, and graphical interface. The current version (4.0) includes the implementation of novel algorithms and third-party tools for genome functional annotation, draft assembly, model refinement, and curation. Such updates increased the user base, resulting in multiple published works, including genome metabolic (re-)annotations and model reconstructions of multiple (lower and higher) eukaryotes and prokaryotes. merlin version 4.0 is the only tool able to perform template based and de novo draft reconstructions, while achieving competitive performance compared to state-of-the art tools both for well and less-studied organisms.

Comprehensive generation, visualization, and reporting of quality control metrics for single-cell RNA sequencing data

Abstract: Single-cell RNA sequencing (scRNA-seq) can be used to gain insights into cellular heterogeneity within complex tissues. However, various technical artifacts can be present in scRNA-seq data and should be assessed before performing downstream analyses. While several tools have been developed to perform individual quality control (QC) tasks, they are scattered in different packages across several programming environments. Here, to streamline the process of generating and visualizing QC metrics for scRNA-seq data, we built the SCTK-QC pipeline within the singleCellTK R package. The SCTK-QC workflow can import data from several single-cell platforms and preprocessing tools and includes steps for empty droplet detection, generation of standard QC metrics, prediction of doublets, and estimation of ambient RNA. It can run on the command line, within the R console, on the cloud platform or with an interactive graphical user interface. Overall, the SCTK-QC pipeline streamlines and standardizes the process of performing QC for scRNA-seq data.

Graphical user interface for SDTrimSP to simulate sputtering, ion implantation and the dynamic effects of ion irradiation

Abstract: SDTrimSP is a popular simulation program to compute several effects of the interaction between an impinging ion and a solid, such as ion implantation ranges, damage formation or sputtering of surface atoms. We now introduce a graphical user interface for SDTrimSP to make its operation more accessible for a broad group of users. It is written as a separate Python program and is not restricted to any specific operating system. The interface allows a quick and easy start as well as the direct evaluation of SDTrimSP simulations. Its capabilities are demonstrated here in the form of several example cases, including the dynamic simulations with SDTrimSP, where ion-induced target changes are taken into account. The presented graphical user interface is made freely available to support a large number of users in performing simulations of ion–solid interaction.

KiMoPack: A python Package for Kinetic Modeling of the Chemical Mechanism

Abstract: Herein, we present KiMoPack, an analysis tool for the kinetic modeling of transient spectroscopic data. KiMoPack enables a state-of-the-art analysis routine including data preprocessing and standard fitting (global analysis), as well as fitting of complex (target) kinetic models, interactive viewing of (fit) results, and multiexperiment analysis via user accessible functions and a graphical user interface (GUI) enhanced interface. To facilitate its use, this paper guides the user through typical operations covering a wide range of analysis tasks, establishes a typical workflow and is bridging the gap between ease of use for less experienced users and introducing the advanced interfaces for experienced users. KiMoPack is open source and provides a comprehensive front-end for preprocessing, fitting and plotting of 2-dimensional data that simplifies the access to a powerful python-based data-processing system and forms the foundation for a well documented, reliable, and reproducible data analysis.

BIDScoin: A User-Friendly Application to Convert Source Data to Brain Imaging Data Structure

Abstract: Analyses of brain function and anatomy using shared neuroimaging data is an important development, and have acquired the potential to be scaled up with the specification of a new Brain Imaging Data Structure (BIDS) standard. To date, a variety of software tools help researchers in converting their source data to BIDS but often require programming skills or are tailored to specific institutes, data sets, or data formats. In this paper, we introduce BIDScoin, a cross-platform, flexible, and user-friendly converter that provides a graphical user interface (GUI) to help users finding their way in BIDS standard. BIDScoin does not require programming skills to be set up and used and supports plugins to extend their functionality. In this paper, we show its design and demonstrate how it can be applied to a downloadable tutorial data set. BIDScoin is distributed as free and open-source software to foster the community-driven effort to promote and facilitate the use of BIDS standard.

Water Quality Predictive Analytics Using an Artificial Neural Network with a Graphical User Interface

Abstract: Since clean water is well known as one of the crucial sources that all living things need in their daily lives, the demand for clean freshwater nowadays has increased. However, water quality is slowly deteriorating due to anthropogenic and natural sources of pollution and contamination. Therefore, this study aims to develop artificial neural network (ANN) models to predict six different water quality parameters in the Langat River, Malaysia. Moreover, an application (app) equipped with a graphical user interface (GUI) was designed and developed to conduct real-time prediction of the water quality parameters by using real-time data as inputs together with the ANN models. As for the results, all of the ANN models achieved high coefficients of determination (R2), which were between 0.9906 and 0.9998, as well as between 0.8797 and 0.9972 for training and testing datasets, respectively. The developed app successfully predicted the outcome based on the run models. The implementation of a GUI-based app in this study enables a simpler and more trouble-free workflow in predicting water quality parameters. By eliminating sophisticated programming subroutines, the prediction process becomes accessible to more people, especially on-site operators and trainees.

Low-Cost Portable ECG Monitoring Device for Inaccessible Areas in Pakistan

Abstract: A need for constant health monitoring system is essential especially for heart diseases which may cause sudden stroke and death. We present in this paper the design and development of a low cost, efficient and user-friendly ECG monitoring device. Most of the heart rate measurement devices and tools available are quite expensive and may not be easily available in some areas. Presented device monitors the patient’s body information using three lead silver chloride ECG disposable electrodes and detects the pulse signal. The detected heart pulse signal is first filtered and then amplified. The device displays the heart signal on a MATLAB graphical user interface while simultaneously showing the digitized pulse rate on a digital LCD. The device was tested on female patients aged 20-24. The results obtained were reliable compared with electrocardiogram reports and similar available devices of much higher development cost.

Microstructure Characterization and Reconstruction in Python: MCRpy

Abstract: Abstract Microstructure characterization and reconstruction (MCR) is an important prerequisite for empowering and accelerating integrated computational materials engineering. Much progress has been made in MCR recently; however, in the absence of a flexible software platform it is difficult to use ideas from other researchers and to develop them further. To address this issue, this work presents MCRpy as an easy-to-use, extensible and flexible open-source MCR software platform. MCRpy can be used as a program with graphical user interface, as a command line tool and as a Python library. The central idea is that microstructure reconstruction is formulated as a modular and extensible optimization problem. In this way, arbitrary descriptors can be used for characterization and arbitrary loss functions combining arbitrary descriptors can be minimized using arbitrary optimizers for reconstructing random heterogeneous media. With stochastic optimizers, this leads to variations of the well-known Yeong–Torquato algorithm. Furthermore, MCRpy features automatic differentiation, enabling the utilization of gradient-based optimizers. In this work, after a brief introduction to the underlying concepts, the capabilities of MCRpy are demonstrated by exemplarily applying it to typical MCR tasks. Finally, it is shown how to extend MCRpy by defining a new microstructure descriptor and readily using it for reconstruction without additional implementation effort.

Linien: A versatile, user-friendly, open-source FPGA-based tool for frequency stabilization and spectroscopy parameter optimization.

Abstract: We present a user-friendly and versatile tool for laser frequency stabilization. Its main focus is spectroscopy locking, but the software is suitable for lock-in techniques in general as well as bare proportional-integral-derivative (PID) operation. Besides allowing for sinusoidal modulation (up to 50 MHz), triangular ramp scanning, in-phase and quadrature demodulation (1-5 f), infinite impulse response, and PID filtering, Linien features two different algorithms for automatic lock point selection; one of them performs time-critical tasks completely on field-programmable gate arrays. Linien is capable of autonomously optimizing spectroscopy parameters by means of machine learning and can measure the error signal's power spectral density. The software is built in a modular way, providing both a graphical user interface as well as a Python scripting interface. It is based on the RedPitaya STEMLab platform but may be ported to different systems.

Psychologically-inspired, unsupervised inference of perceptual groups of GUI widgets from GUI images

Abstract: Graphical User Interface (GUI) is not merely a collection of individual and unrelated widgets, but rather partitions discrete widgets into groups by various visual cues, thus forming higher-order perceptual units such as tab, menu, card or list. The ability to automatically segment a GUI into perceptual groups of widgets constitutes a fundamental component of visual intelligence to automate GUI design, implementation and automation tasks. Although humans can partition a GUI into meaningful perceptual groups of widgets in a highly reliable way, perceptual grouping is still an open challenge for computational approaches. Existing methods rely on ad-hoc heuristics or supervised machine learning that is dependent on specific GUI implementations and runtime information. Research in psychology and biological vision has formulated a set of principles (i.e., Gestalt theory of perception) that describe how humans group elements in visual scenes based on visual cues like connectivity, similarity, proximity and continuity. These principles are domain-independent and have been widely adopted by practitioners to structure content on GUIs to improve aesthetic pleasantness and usability. Inspired by these principles, we present a novel unsupervised image-based method for inferring perceptual groups of GUI widgets. Our method requires only GUI pixel images, is independent of GUI implementation, and does not require any training data. The evaluation on a dataset of 1,091 GUIs collected from 772 mobile apps and 20 UI design mockups shows that our method significantly outperforms the state-of-the-art ad-hoc heuristics-based baseline. Our perceptual grouping method creates opportunities for improving UI-related software engineering tasks.

<i>SAXSDOG</i>: open software for real-time azimuthal integration of 2D scattering images

Abstract: In situ small- and wide-angle scattering experiments at synchrotrons often result in massive quantities of data within just seconds. Especially during such beamtimes, processing of the acquired data online, without appreciable delay, is key to obtaining feedback on the failure or success of the experiment. This had led to the development of SAXSDOG, a Python-based environment for real-time azimuthal integration of large-area scattering images. The software is primarily designed for dedicated data pipelines: once a scattering image is transferred from the detector onto the storage unit, it is automatically integrated and pre-evaluated using integral parameters within milliseconds. The control and configuration of the underlying server-based processes is achieved via a graphical user interface, SAXSLEASH, which visualizes the resulting 1D data together with integral classifiers in real time. SAXSDOG further includes a portable 'take-home' version for users that runs on standalone computers, enabling its use in laboratories or at the preferred workspace.

Analysis of a User Interface Based on Multimodal Interaction to Control a Robotic Arm for EOD Applications

Abstract: A global human–robot interface that meets the needs of Technical Explosive Ordnance Disposal Specialists (TEDAX) for the manipulation of a robotic arm is of utmost importance to make the task of handling explosives safer, more intuitive and also provide high usability and efficiency. This paper aims to evaluate the performance of a multimodal system for a robotic arm that is based on Natural User Interface (NUI) and Graphical User Interface (GUI). The mentioned interfaces are compared to determine the best configuration for the control of the robotic arm in Explosive Ordnance Disposal (EOD) applications and to improve the user experience of TEDAX agents. Tests were conducted with the support of police agents Explosive Ordnance Disposal Unit-Arequipa (UDEX-AQP), who evaluated the developed interfaces to find a more intuitive system that generates the least stress load to the operator, resulting that our proposed multimodal interface presents better results compared to traditional interfaces. The evaluation of the laboratory experiences was based on measuring the workload and usability of each interface evaluated.

New Fuzzy-AHP Matlab based graphical user interface (GUI) for a broad range of users: Sample applications in the environmental field

Abstract: Fuzzy-AHP (analytical hierarchy process) is a powerful method for dealing with subjective information. This popular hybrid approach is widely applied in medical and health science, and industrial management, mainly agriculture and environmental sciences. However, it is a complex, time-consuming method, which has induced us to try and optimize the decision-support system process. We create the Fuzzy-AHP algorithm and program in Matlab software, and convert it with the Matlab based graphical user interface (GUI) application. This is a new desktop tool with a wide selection of applications to help decision-makers prioritize choices and/or criteria goals based on expert judgments imported from Excel and a number of criteria. The new technique is designed to allow experts to fill the matrix judgment from both sides depending on the importance of criteria selection. Also, an optional alpha index to define stable or unstable conditions was requested for advanced users. The application was tested and applied in forest recreation and agroforestry case studies. The user-friendly Fuzzy-AHP Matlab GUI facilitates the process analysis speedily and offers an innovative way of enhancing the uncertainty to find the best compromise among experts. The tool is useful for optimizing the decision-support system process in many different fields.

<tt>DIRECTGO</tt> : A New <tt>DIRECT</tt> -Type <tt>MATLAB</tt> Toolbox for Derivative-Free Global Optimization

Abstract: In this work, we introduce DIRECTGO , a new MATLAB toolbox for derivative-free global optimization. DIRECTGO collects various deterministic derivative-free DIRECT -type algorithms for box-constrained, generally constrained, and problems with hidden constraints. Each sequential algorithm is implemented in two ways: using static and dynamic data structures for more efficient information storage and organization. Furthermore, parallel schemes are applied to some promising algorithms within DIRECTGO . The toolbox is equipped with a graphical user interface (GUI), ensuring the user-friendly use of all functionalities available in DIRECTGO . Available features are demonstrated in detailed computational studies using a comprehensive DIRECTGOLib v1.0 library of global optimization test problems. Additionally, 11 classical engineering design problems illustrate the potential of DIRECTGO to solve challenging real-world problems. Finally, the appendix gives examples of accompanying MATLAB programs and provides a synopsis of its use on the test problems with box and general constraints.

Development of a tool to optimize economic and environmental feasibility of food waste chains

Abstract: Abstract The Sustainable Development Goal 12.3 focuses on food and its inedible parts that exit the supply chain and thus are lost or wasted. This work addresses the food waste problem by presenting the development of a tool to design business models to reduce the production of food waste. This has been developed within the LIFE16 project iRexfo, coordinated by the University of Perugia. The tool aims at transferring the results obtained in a pilot region (Umbria, Italy) to 4 other regions in Europe. It has been coded in Python and has a graphical user interface (GUI) to insert inputs and display outputs. The GUI has been developed in FLASK and it is hosted in the website of PythonAnywhere. A case study on the application of the software is also presented, mainly based on data retrieved in the Umbria region, Italy. Together with economic analysis, also, environmental assessment is performed.

A taxonomy of metrics for GUI-based testing research: A systematic literature review

Abstract: GUI-based testing is a sub-field of software testing research that has emerged in the last three decades. GUI-based testing techniques focus on verifying the functional conformance of the system under test (SUT) through its graphical user interface. However, despite the research domains growth, studies in the field have low reproducibility and comparability. One observed cause of these phenomena is identified as a lack of research rigor and commonly used metrics, including coverage metrics. We aim to identify the most commonly used metrics in the field and formulate a taxonomy of coverage metrics for GUI-based testing research. We adopt an evidence-based approach to build the taxonomy through a systematic literature review of studies in the GUI-based testing domain. Identified papers are then analyzed with Open and Axial Coding techniques to identify hierarchical and mutually exclusive categories of metrics with common characteristics, usages, and applications. Through the analysis of 169 papers and 315 metric definitions, we obtained a taxonomy with 55 codes (common names for metrics), 17 metric categories, and 4 higher level categories: Functional Level, GUI Level, Model Level and Code Level. We measure a higher number of mentions of Model and Code level metrics over Functional and GUI level metrics. We propose a taxonomy for use in future GUI-based testing research to improve the general quality of studies in the domain. In addition, the taxonomy is perceived to help enable more replication studies as well as macro-analysis of the current body of research.

An interactive graphical interface tool for parameter calibration, sensitivity analysis, uncertainty analysis, and visualization for the Soil and Water Assessment Tool

Abstract: The Soil and Water Assessment Tool (SWAT) is one of the most widely used and well-tested eco-hydrological models. However, parameter calibration, sensitivity analysis and uncertainty analysis remain among the most challenging tasks. Existing SWAT parameter calibration, sensitivity analysis, and uncertainty analysis tools are either commercial products or free tools with limited options. This study demonstrates an interactive graphical user interface tool in the R environment for SWAT parameter calibration, sensitivity and uncertainty analyses, and visualization, called R-SWAT. Different R functions/packages for parameter calibration, sensitivity analysis, and uncertainty analysis have been incorporated into R-SWAT. Third-party packages can be integrated into R-SWAT with minimum effort. The application of R-SWAT for a test case study demonstrates its functionalities. In general, R-SWAT (1) is a potential platform for developing and testing new sensitivity or optimization packages, and (2) promotes the understanding of hydrological processes with open-source SWAT and R.

DeepImageTranslator: A free, user-friendly graphical interface for image translation using deep-learning and its applications in 3D CT image analysis

Abstract: The advent of deep-learning has set new standards in an array of image translation applications. At present, the use of these methods often requires computer programming experience. Non-commercial programs with graphical interface usually do not allow users to fully customize their deep-learning pipeline. Therefore, our primary objective is to provide a simple graphical interface that allows researchers with no programming experience to easily create, train, and evaluate custom deep-learning models for image translation. We also aimed to test the applicability of our tool in CT image semantic segmentation and noise reduction. DeepImageTranslator was implemented using the Tkinter library, the standard Python interface to the Tk graphical user interface toolkit; backend computations were implemented using data augmentation packages such as Pillow, Numpy, OpenCV, Augmentor, Tensorflow, and Keras libraries. Convolutional neural networks (CNNs) were trained using DeepImageTranslator. The effects of data augmentation, deep-supervision, and sample size on model accuracy were also systematically assessed. The DeepImageTranslator a simple tool that allows users to customize all aspects of their deep-learning pipeline, including the CNN, training optimizer, loss function, and the types of training image augmentation scheme. We showed that DeepImageTranslator can be used to achieve state-of-the-art accuracy and generalizability in semantic segmentation and noise reduction. Highly accurate 3D segmentation models for body composition can be obtained using training sample sizes as small as 17 images. In conclusion, an open-source deep-learning tool for accurate image translation with a user-friendly graphical interface was presented and evaluated. This standalone software can be downloaded at: https://sourceforge.net/projects/deepimagetranslator/.

STRIKE-GOLDD 4.0: user-friendly, efficient analysis of structural identifiability and observability

Abstract: Abstract Motivation STRIKE-GOLDD is a toolbox that analyses the structural identifiability and observability of possibly non-linear, non-rational ODE models that may have known and unknown inputs. Its broad applicability comes at the expense of a lower computational efficiency than other tools. Results STRIKE-GOLDD 4.0 includes a new algorithm, ProbObsTest, specifically designed for the analysis of rational models. ProbObsTest is significantly faster than the previously available FISPO algorithm when applied to computationally expensive models. Providing both algorithms in the same toolbox allows combining generality and computational efficiency. STRIKE-GOLDD 4.0 is implemented as a Matlab toolbox with a user-friendly graphical interface. Availability and implementation STRIKE-GOLDD 4.0 is a free and open-source tool available under a GPLv3 license. It can be downloaded from GitHub at https://github.com/afvillaverde/strike-goldd. Supplementary information Supplementary data are available at Bioinformatics online.