Interactive Graphical Interface Research Articles

Computer Vision Based Robotic Arm Controlled Using Interactive GUI

This paper presents the design and implementation of a robotic vision system operated using an interactive Graphical User Interface (GUI) application. As robotics continue to become a more integral part of the industrial complex, there is a need for automated systems that require minimal to no user training to operate. With this motivation in mind, the system is designed so that a beginner user can operate the device with very little instruction. The application allows users to determine their desired object, which will be picked up and placed by a robotic arm into the target location. The application allows users to filter objects based on color, shape, and size. The filtering along the three parameters is done by employing a Hue-Saturation-Value (HSV) mode color detection algorithm, shape detection algorithm, size determining algorithm. Once the target object is identified, a centroid detection algorithm is employed to find the object’s center coordinates. An inverse kinematic algorithm is used to ascertain the robotic arm’s joint positions for picking the object. The arm then goes through a set of preset positions to pick up the object, place the object, and then return the arm to the initial position. The joint coordinates are forwarded to a microcontroller that sets the arm’s joint angle at each position.

Development of 3D models for faculty of education database system via monitor’s graphical user interface interactive for perception and utilization

This study is a research and development study that used systematic approaches as an operational concept. The objectives of the study included: (1) To study the usage demands of an on-screen interactive Graphical User Interface (GUI) for the Faculty of Education database. (2) To create 3D models and study their efficiency in the usage of an on-screen interactive GUI for the Faculty of Education database. (3) To evaluate the perception and utilization of 3D models in the usage of an on-screen interactive GUI for the Faculty of Education database. The population in this study included; (1) 100 staff and students in the Faculty of Education – who were selected using Purposive Sampling to study usage demands of an on-screen interactive GUI for the Faculty of Education database. (2) 5 experts and 40 staff and students of the Faculty of Education – who were selected using Purposive Sampling to study the efficiency of 3D models in the usage of an on-screen interactive GUI for the Faculty of Education database. (3) 300 staff and students of Ramkhamhaeng University who used 3D models with the on-screen interactive GUI of the Faculty of Education database within the 1-month test period of the study. The research instruments used in this study were: (1) a questionnaire about usage demands of an on-screen interactive GUI for the Faculty of Education database, (2) an expert opinion evaluation form, and (3) an assessment form for perception and utilization of 3D models in the usage of an on-screen interactive GUI for the Faculty of Education database – all of which were found with .930 reliability and item discrimination values between .71 - .85.

MethPanel: a parallel pipeline and interactive analysis tool for multiplex bisulphite PCR sequencing to assess DNA methylation biomarker panels for disease detection.

SummaryDNA methylation patterns in a cell are associated with gene expression and the phenotype of a cell, including disease states. Bisulphite PCR sequencing is commonly used to assess the methylation profile of genomic regions between different cells. Here we have developed MethPanel, a computational pipeline with an interactive graphical interface to rapidly analyse multiplex bisulphite PCR sequencing data. MethPanel comprises a complete analysis workflow from genomic alignment to DNA methylation calling and supports an unlimited number of PCR amplicons and input samples. MethPanel offers important and unique features, such as calculation of an epipolymorphism score and bisulphite PCR bias correction capabilities, and is designed so that the methylation data from all samples can be processed in parallel. The outputs are automatically forwarded to a shinyApp for convenient display, visualization and remotely sharing data with collaborators and clinicians.Availabilityand implementationMethPanel is freely available at https://github.com/thinhong/MethPanel.Supplementary informationSupplementary data are available at Bioinformatics online.

SEPIA—Susceptibility mapping pipeline tool for phase images

Quantitative susceptibility mapping (QSM) is a physics-driven computational technique that has a high sensitivity in quantifying iron deposition based on MRI phase images. Furthermore, it has a unique ability to distinguish paramagnetic and diamagnetic contributions such as haemorrhage and calcification based on image contrast. These properties have contributed to a growing interest to use QSM not only in research but also in clinical applications. However, it is challenging to obtain high quality susceptibility map because of its ill-posed nature, especially for researchers who have less experience with QSM and the optimisation of its pipeline. In this paper, we present an open-source processing pipeline tool called SuscEptibility mapping PIpeline tool for phAse images (SEPIA) dedicated to the post-processing of MRI phase images and QSM. SEPIA connects various QSM toolboxes freely available in the field to offer greater flexibility in QSM processing. It also provides an interactive graphical user interface to construct and execute a QSM processing pipeline, simplifying the workflow in QSM research. The extendable design of SEPIA also allows developers to deploy their methods in the framework, providing a platform for developers and researchers to share and utilise the state-of-the-art methods in QSM.

ANALISIS MODEL ANTREAN NON-POISSON DAN UKURAN KINERJA SISTEM BERBASIS GUI WEB INTERAKTIF MENGGUNAKAN R-SHINY (Studi Kasus: Bus di Terminal Penggaron Kota Semarang)

Since September 1, 2018, The Semarang City Government has diverted intercity bus stop within the province from Terboyo Terminal to Penggaron Terminal, resulting in an imbalance of movement and capacity of the Penggaron Terminal which causes queue of bus. Non-Poisson queue is a queue model in which the arrival and service distribution do not have a Poisson distribution or do not have an Exponential distribution. The study was conducted on buses entering the Penggaron Bus Station with the destination of Jepara, Kedungjati, Juwangi, Yogyakarta, Kudus/Pati/Lasem, Pekalongan/Tegal, and Purwokerto/Purworejo. The main goal of this project is to identify the queue model of Non-Poisson and calculate the measure of system performance using the GUI R. One of the programs in R that can create an interactive web-based GUI (Graphical User Interface) is R-Shiny. R-Shiny is a toolkit of R programs that can be used to create online programs. The distribution test obtained using the EasyFit program. The bus queue model of Jepara is (DAGUM/GEV/4):(GD/∞/∞), the queue model of Kedungjati is (GPD/ DAGUM/1):(GD/∞/∞), the queue model of Juwangi is (GEV/ GEV/1):(GD/∞/∞), the queue model of Yogyakarta is (DAGUM/ DAGUM/1) : (GD/∞/∞), the queue model of Kudus/Pati/Lasem is (DAGUM/GEV/1):(GD/∞/∞), the queue model of Pekalongan/Tegal is (GEV/DAGUM/1):(GD/∞/∞), and the queue model of Purwokerto/Purworejo is (GPD/DAGUM/1) : (GD/∞/∞).

The antiSMASH database version 3: increased taxonomic coverage and new query features for modular enzymes.

Microorganisms produce natural products that are frequently used in the development of antibacterial, antiviral, and anticancer drugs, pesticides, herbicides, or fungicides. In recent years, genome mining has evolved into a prominent method to access this potential. antiSMASH is one of the most popular tools for this task. Here, we present version 3 of the antiSMASH database, providing a means to access and query precomputed antiSMASH-5.2-detected biosynthetic gene clusters from representative, publicly available, high-quality microbial genomes via an interactive graphical user interface. In version 3, the database contains 147 517 high quality BGC regions from 388 archaeal, 25 236 bacterial and 177 fungal genomes and is available at https://antismash-db.secondarymetabolites.org/.

DescribePROT: database of amino acid-level protein structure and function predictions.

We present DescribePROT, the database of predicted amino acid-level descriptors of structure and function of proteins. DescribePROT delivers a comprehensive collection of 13 complementary descriptors predicted using 10 popular and accurate algorithms for 83 complete proteomes that cover key model organisms. The current version includes 7.8 billion predictions for close to 600 million amino acids in 1.4 million proteins. The descriptors encompass sequence conservation, position specific scoring matrix, secondary structure, solvent accessibility, intrinsic disorder, disordered linkers, signal peptides, MoRFs and interactions with proteins, DNA and RNAs. Users can search DescribePROT by the amino acid sequence and the UniProt accession number and entry name. The pre-computed results are made available instantaneously. The predictions can be accesses via an interactive graphical interface that allows simultaneous analysis of multiple descriptors and can be also downloaded in structured formats at the protein, proteome and whole database scale. The putative annotations included by DescriPROT are useful for a broad range of studies, including: investigations of protein function, applied projects focusing on therapeutics and diseases, and in the development of predictors for other protein sequence descriptors. Future releases will expand the coverage of DescribePROT. DescribePROT can be accessed at http://biomine.cs.vcu.edu/servers/DESCRIBEPROT/.

Pre-clustering data sets using cluster4x improves the signal-to-noise ratio of high-throughput crystallography drug-screening analysis.

Drug and fragment screening at X-ray crystallography beamlines has been a huge success. However, it is inevitable that more high-profile biological drug targets will be identified for which high-quality, highly homogenous crystal systems cannot be found. With increasing heterogeneity in crystal systems, the application of current multi-data-set methods becomes ever less sensitive to bound ligands. In order to ease the bottleneck of finding a well behaved crystal system, pre-clustering of data sets can be carried out using cluster4x after data collection to separate data sets into smaller partitions in order to restore the sensitivity of multi-data-set methods. Here, the software cluster4x is introduced for this purpose and validated against published data sets using PanDDA, showing an improved total signal from existing ligands and identifying new hits in both highly heterogenous and less heterogenous multi-data sets. cluster4x provides the researcher with an interactive graphical user interface with which to explore multi-data set experiments.

A cloud-computing platform for developing and evaluating vocal biomarkers based on home audio recordings: Resources for large-scale data processing and analysis

This presentation describes the design and construction of a comprehensive cloud-computing platform for implementing and evaluating vocal biomarkers, both for assessing typical development of speech and language and detecting deviations in autism. As part of a prospective longitudinal study of early vocal development (NIH P50 MH100029), whole-day home audio recordings were collected from more than 300 children every month from birth to three years using LENA, providing long-term, large-scale sampling of each child's natural environment. The database contains more than 40 000 h of raw audio data, post-processed acoustic measures, event timing statistics, hand-coded and automated annotations, as well as sociodemographic and clinical metadata, the storage, integration and processing of which has presented significant new challenges. Flexible cloud solutions have been adopted to allow secure cross-platform shared access and referencing of the data. Customized modular “C” code libraries for physical modeling, spectral analysis, temporal event labeling, voice activity detection, speaker diarization and developmental profiling have been developed, based on standard BLAS/LAPACK libraries optimized for device-independent virtual machines, and integrated with an interactive graphical interface for signal analysis and labeling. Resources and specific challenges for large-scale analysis of infant vocalizations will be discussed.

DEVELOPMENT OF A SMART IoT-BASED HOME AUTOMATION SYSTEM

Advances in technology such as internet-of-things (IoT) and its wide-ranging applications have made it necessary to have smart homes. The ease with which home appliances can be remotely monitored and controlled improves the standard of living, as automatic processes are used to replace manual efforts to perform some basic functions in the home. The busy schedules of individuals have heightened the pressing need for intelligent homes. Household owners tend to pay more for electricity consumption even though they were not physically present at home, but their devices were either intentionally or ignorantly left ON when not in use. Elderly people and physically challenged individuals find it hard to execute fundamental tasks manually, such as switching ON/OFF lights, fan, TV set, and other home appliances. In this work, a smart home that can remotely automate the operation of home appliances and smartly make decisions without human interference is proposed. In addition, this paper presents a smart home system that has an interactive graphical user interface on an android device to allow the user to choose whether to remotely control and monitor the home from their android device or to enable automatic control using sensors that are interfaced with a home-based PIC microcontroller. The temperature sensor, the light sensor, the passive infrared sensor (PIR) and the Wi-Fi module, which enable internet connection between the microcontroller and the Android application, are all interfaced with the PIC microcontroller at the receiving end, while at the transmitting end, the graphical user interface application on the android device sends commands to the microcontroller to which the sensors and loads are interfaced. The proposed system will be very helpful in energy conservation, while ease of remotely operating home appliances is also provided to both physically challenged and healthy individuals.

VizSciFlow: A Visually Guided Scripting Framework for Supporting Complex Scientific Data Analysis

Scientific workflow management systems such as Galaxy, Taverna and Workspace, have been developed to automate scientific workflow management and are increasingly being used to accelerate the specification, execution, visualization, and monitoring of data-intensive tasks. For example, the popular bioinformatics platform Galaxy is installed on over 168 servers around the world and the social networking space myExperiment shares almost 4,000 Galaxy scientific workflows among its 10,665 members. Most of these systems offer graphical interfaces for composing workflows. However, while graphical languages are considered easier to use, graphical workflow models are more difficult to comprehend and maintain as they become larger and more complex. Text-based languages are considered harder to use but have the potential to provide a clean and concise expression of workflow even for large and complex workflows. A recent study showed that some scientists prefer script/text-based environments to perform complex scientific analysis with workflows. Unfortunately, such environments are unable to meet the needs of scientists who prefer graphical workflows. In order to address the needs of both types of scientists and at the same time to have script-based workflow models because of their underlying benefits, we propose a visually guided workflow modeling framework that combines interactive graphical user interface elements in an integrated development environment with the power of a domain-specific language to compose independently developed and loosely coupled services into workflows. Our domain-specific language provides scientists with a clean, concise, and abstract view of workflow to better support workflow modeling. As a proof of concept, we developed VizSciFlow, a generalized scientific workflow management system that can be customized for use in a variety of scientific domains. As a first use case, we configured and customized VizSciFlow for the bioinformatics domain. We conducted three user studies to assess its usability, expressiveness, efficiency, and flexibility. Results are promising, and in particular, our user studies show that VizSciFlow is more desirable for users to use than either Python or Galaxy for solving complex scientific problems.

MEPHAS: an interactive graphical user interface for medical and pharmaceutical statistical analysis with R and Shiny

BackgroundEven though R is one of the most commonly used statistical computing environments, it lacks a graphical user interface (GUI) that appeals to students, researchers, lecturers, and practitioners in medicine and pharmacy for conducting standard data analytics. Current GUIs built on top of R, such as EZR and R-Commander, aim to facilitate R coding and visualization, but most of the functionalities are still accessed through a command-line interface (CLI). To assist practitioners of medicine and pharmacy and researchers to run most routines in fundamental statistical analysis, we developed an interactive GUI; i.e., MEPHAS, to support various web-based systems that are accessible from laptops, workstations, or tablets, under Windows, macOS (and IOS), or Linux. In addition to fundamental statistical analysis, advanced statistics such as the extended Cox regression and dimensional analyses including partial least squares regression (PLS-R) and sparse partial least squares regression (SPLS-R), are also available in MEPHAS.ResultsMEPHAS is a web-based GUI (https://alain003.phs.osaka-u.ac.jp/mephas/) that is based on a shiny framework. We also created the corresponding R package mephas (https://mephas.github.io/). Thus far, MEPHAS has supported four categories of statistics, including probability, hypothesis testing, regression models, and dimensional analyses. Instructions and help menus were accessible during the entire analytical process via the web-based GUI, particularly advanced dimensional data analysis that required much explanation. The GUI was designed to be intuitive for non-technical users to perform various statistical functions, e.g., managing data, customizing plots, setting parameters, and monitoring real-time results, without any R coding from users. All generated graphs can be saved to local machines, and tables can be downloaded as CSV files.ConclusionMEPHAS is a free and open-source web-interactive GUI that was designed to support statistical data analyses and prediction for medical and pharmaceutical practitioners and researchers. It enables various medical and pharmaceutical statistical analyses through interactive parameter settings and dynamic visualization of the results.

COVTree: Coevolution in OVerlapped sequences by Tree analysis server.

Overlapping genes are commonplace in viruses and play an important role in their function and evolution. For these genes, molecular coevolution may be seen as a mechanism to decrease the evolutionary constraints of amino acid positions in the overlapping regions and to tolerate or compensate unfavorable mutations. Tracing these mutational sites, could help to gain insight on the direct or indirect effect of the mutations in the corresponding overlapping proteins. In the past, coevolution analysis has been used to identify residue pairs and coevolutionary signatures within or between proteins that served as markers of physical interactions and/or functional relationships. Coevolution in OVerlapped sequences by Tree analysis (COVTree) is a web server providing the online analysis of coevolving amino-acid pairs in overlapping genes, where residues might be located inside or outside the overlapping region. COVTree is designed to handle protein families with various characteristics, among which those that typically display a small number of highly conserved sequences. It is based on BIS2, a fast version of the coevolution analysis tool Blocks in Sequences (BIS). COVTree provides a rich and interactive graphical interface to ease biological interpretation of the results and it is openly accessible at http://www.lcqb.upmc.fr/COVTree/.

HemoSYS: An Image‐based Toolkit for Quantifying Hemodynamics in the Microcirculation

ObjectiveTo develop an easy‐to‐use image‐based toolkit for quantifying spatiotemporal hemodynamic changes in the healthy and pathologic microcirculation.MethodsWe combined the capabilities of two well‐known image processing platforms: Matlab® (MathWorks, MA) and ImageJ into a single framework, and created an interactive graphical user interface (GUI) to manage all aspects of user interactions. The resulting toolkit for quantifying hemodynamic changes, HemoSYS, can be utilized without any prior programming knowledge, and consists of five analysis modules: propagation, clustering, coupling, perturbation, and Fourier. We demonstrate the utility of HemoSYS by using it to quantify hemodynamic changes within the tumor microenvironment (TME) of a murine breast cancer model. To acquire multi‐variable microcirculatory dynamics of the TME, we used a multi‐contrast optical imaging system and obtained wide field (i.e. 5 × 7 mm2) images of tumor extent via fluorescence (FL) imaging of GFP tagged tumor cells, and concurrent image‐sequences of tumor microvasculature or blood volume (BV) via hemoglobin‐based intrinsic optical signal (IOS) imaging, intravascular oxygen saturation (HbSat) via IOS imaging, and blood flow (BF) via laser speckle contrast (LSC) imaging every 30 seconds, for 1 hour.ResultsFig. 1 shows a schematic of HemoSYS illustrating its input data and capabilities. Using HemoSYS on a cohort of 5 animals, we identified the tumor extent and interrogated: (i) the propagation characteristics of an acute hypoxic episode; (ii) the formation and cessation of clusters with distinct microcirculatory dynamics; (iii) the dysregulation of blood flow; (iv) the multi‐variable hemodynamic response to carbogen gas inhalation;and (v) the heterogeneity of microcirculatory dynamics in the frequency domain.ConclusionHemoSYS (freely available upon request) enables characterization of hemodynamic changes in microvascular beds using a systems biology approach. It can be used by anyone interested in quantifying hemodynamic changes from imaging data because it does not require any programming experience. While we demonstrated its utility using wide‐field optical imaging data, HemoSYS could be readily modified to accept input data from additional imaging modalities such as MR, PET, and Photoacoustic imaging. We believe that HemoSYS will become a tool‐of‐choice for image‐based characterization of the microcirculation in any preclinical disease model or tissue bed.Support or Funding InformationThis work was supported by NCI 1R01CA196701, 5R01CA138264 and a Kavli Neuroscience Distinguished Fellowship (JS).Schematic of HemoSYS illustrating its inputs and capabilities.HemoSYS accepts a broad range of inputs, from static images indicating an area of interest (e.g. the tumor extent) to multiple image‐sequences showing concurrent spatiotemporal changes in multiple hemodynamic variables (e.g. BV, HbSat and BF). One can then interactively use HemoSYS’s five modules (i.e. propagation, clustering, coupling, perturbation and Fourier) to quantify and characterize the underlying microcirculation.Figure 1

Efficient Pharmacokinetic Modeling Workflow With the MonolixSuite: A Case Study of Remifentanil.

MonolixSuite is a software widely used for model‐based drug development. It contains interconnected applications for data visualization, noncompartmental analysis, nonlinear mixed effect modeling, and clinical trial simulations. Its main assets are ease of use via an interactive graphical interface, computation speed, and efficient parameter estimation even for complex models. This tutorial presents a step‐by‐step pharmacokinetic (PK) modeling workflow using MonolixSuite, including how to visualize the data, set up a population PK model, estimate parameters, and diagnose and improve the model incrementally.

UTILIZING LANDSAT AND SENTINEL-2 TO REMOTELY MONITOR AND EVALUATE THE PERFORMANCE OF WINTER COVER CROPS THROUGHOUT MARYLAND

Abstract. Winter cover crops have been shown to limit erosion and nutrient runoff from agricultural land. To promote their usage, the Maryland Department of Agriculture (MDA) subsidizes farmers who plant cover crops. Conventional verification of cover crop planting and analysis of subsequent crop performance requires on-the-ground fieldwork, which is costly and labor intensive. In partnership with the MDA, NASA's DEVELOP program utilized imagery from Landsat 5, Landsat 8, and the European Space Agency’s Sentinel-2 to create a decision support tool for satellite-based monitoring of cover crop performance throughout Maryland. Our teams created CCROP, an interactive graphical user interface, in Google Earth Engine which analyzes satellite imagery to calculate the normalized difference vegetation index (NDVI) of fields across the state. Linear regression models were applied to convert NDVI to estimates of crop biomass and percent green ground cover, with measure of fit (R2) values ranging from 0.4 to 0.7. These crop metrics were implemented into an interactive filtering tool within CCROP which allows users to examine cover crop performance based on a variety of growing parameters. CCROP also includes a time series analysis routine for examining the progression of NDVI throughout the spring to help determine farmer-induced termination dates of cover crops. With this decision support tool, the MDA can analyze the effectiveness of cover crops throughout the state with reduced need to manually spot-check enrolled production fields, and can identify variables influencing overall cover crop performance to optimize implementation of their winter cover crop program via adaptive management approaches.

ProQEXAFS: a highly optimized parallelized rapid processing software for QEXAFS data.

The high temporal resolution in data acquisition, possible in the quick-scanning EXAFS (QEXAFS) mode of operation, provides new challenges in efficient data processing methods. Here a new approach is developed that combines an easy to use interactive graphical interface with highly optimized and fully parallelized Python-based routines for extracting, normalizing and interpolating oversampled time-resolved XAS spectra from a raw binary stream of data acquired during operando QEXAFS studies. The programs developed are freely available via a Github repository.

A Latent Feature-Based Multimodality Fusion Method for Theme Classification on Web Map Service

Massive maps have been shared as Web Map Service (WMS) from various providers, which could be used to facilitate people's daily lives and support space analysis and management. The theme classification of maps could help users efficiently find maps and support theme-related applications. Traditionally, metadata is usually used in analyzing maps content, few papers use maps, especially legends. In fact, people usually considers metadata, maps and legends together to understand what maps tell, however, no study has tried to exploit how to combine them. This paper proposes a method to fuse them with the purpose of classifying map themes, named latent feature based multimodality fusion for theme classification (LFMF-TC). Firstly, a multimodal dataset is created that supports the supervised classification on map themes. Secondly, textual and visual features are designed for metadata, maps, and legends using some advanced techniques. Thirdly, a latent feature based fusion method is proposed to fuse the multimodal features on the feature level. Finally, a neural network classifier is implemented using supervised learning on the multimodal dataset. In addition, a web-based collaboration platform is developed to facilitate users in labeling multimodal samples through an interactive Graphical User Interface (GUI). Extensive experiments are designed and implemented, whose results prove that LFMF-TC could significantly improve the classification accuracy. In theory, the LFMF-TC could be used for other applications with few modifications.

Modeling the transfer of potassium monophosphate with irrigation water in drip irrigation and sprinkling

Fertigation practically always allows us to simultaneously solve a wide range of problems of supplying plants with mineral substances. It is due to the possibility to localize the application area in accordance with the structural features of the root system of the plant. A review of the studies on modeling and calculating the transfer of nutrients shows that spatial inhomogeneity of nutrients distribution may lead to their excess in wrong soil areas. Time intervals and volumes of applying dissolved fertilizers determine the not yet completely studied dynamics of concentration of the nutrition elements in the root area. Formation of the root system is under a strong influence of the boundaries of the wetting contour, since after the irrigation and soil drying nutrients tend to concentrate in this particular area. The results of transfer modeling showed significant differences in the final distribution of potassium monophosphate in soil depending on the initial distribution of moisture there. This can be pre-estimated and calculated. The designed software programme for modeling nutrients transfer with irrigation water allows the user to set various initial wetting gradients depending on the depth, the intervals between the drippers, the intensity and duration of watering. The calculations are made considering the basic hydrophysical soil characteristic and hydraulic conductivity function. The software is equipped with an interactive graphic interface for primary data processing, soil profile discretization and graphic representation of the results.

MLDSP-GUI: an alignment-free standalone tool with an interactive graphical user interface for DNA sequence comparison and analysis.

Machine Learning with Digital Signal Processing and Graphical User Interface (MLDSP-GUI) is an open-source, alignment-free, ultrafast, computationally lightweight, and standalone software tool with an interactive GUI for comparison and analysis of DNA sequences. MLDSP-GUI is a general-purpose tool that can be used for a variety of applications such as taxonomic classification, disease classification, virus subtype classification, evolutionary analyses, among others. MLDSP-GUI is open-source, cross-platform compatible, and is available under the terms of the Creative Commons Attribution 4.0 International license (http://creativecommons.org/licenses/by/4.0/). The executable and dataset files are available at https://sourceforge.net/projects/mldsp-gui/. Supplementary data are available at Bioinformatics online.