scholarly journals G4Hunter web application: a web server for G-quadruplex prediction

2019 ◽  
Vol 35 (18) ◽  
pp. 3493-3495 ◽  
Author(s):  
Václav Brázda ◽  
Jan Kolomazník ◽  
Jiří Lýsek ◽  
Martin Bartas ◽  
Miroslav Fojta ◽  
...  
Keyword(s):  
Data Storage ◽  
Web Application ◽  
Data Representation ◽  
Complete Characterization ◽  
Supplementary Information ◽  
Web Based ◽  
Rna Molecules ◽  
Dna And Rna ◽  
Sorting Data ◽  
User Friendly

Abstract Motivation Expanding research highlights the importance of guanine quadruplex structures. Therefore, easy-accessible tools for quadruplex analyses in DNA and RNA molecules are important for the scientific community. Results We developed a web version of the G4Hunter application. This new web-based server is a platform-independent and user-friendly application for quadruplex analyses. It allows retrieval of gene/nucleotide sequence entries from NCBI databases and provides complete characterization of localization and quadruplex propensity of quadruplex-forming sequences. The G4Hunter web application includes an interactive graphical data representation with many useful options including visualization, sorting, data storage and export. Availability and implementation G4Hunter web application can be accessed at: http://bioinformatics.ibp.cz. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals G4Killer web application: a tool to design G-quadruplex mutations

2020 ◽  
Vol 36 (10) ◽  
pp. 3246-3247
Author(s):  
Vaclav Brazda ◽  
Jan Kolomaznik ◽  
Jean-Louis Mergny ◽  
Jiri Stastny
Keyword(s):  
Dna Sequences ◽  
Web Application ◽  
Rational Design ◽  
Therapeutic Potential ◽  
Supplementary Information ◽  
Web Tool ◽  
Web Based ◽  
Dna Structures ◽  
G Quadruplex ◽  
User Friendly

Abstract Motivation G-quadruplexes (G4) are important regulatory non-B DNA structures with therapeutic potential. A tool for rational design of mutations leading to decreased propensity for G4 formation should be useful in studying G4 functions. Although tools exist for G4 prediction, no easily accessible tool for the rational design of G4 mutations has been available. Results We developed a web-based tool termed G4Killer that is based on the G4Hunter algorithm. This new tool is a platform-independent and user-friendly application to design mutations crippling G4 propensity in a parsimonious way (i.e., keeping the primary sequence as close as possible to the original one). The tool is integrated into our DNA analyzer server and allows for generating mutated DNA sequences having the desired lowered G4Hunter score with minimal mutation steps. Availability and implementation The G4Killer web tool can be accessed at: http://bioinformatics.ibp.cz. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals An Interactive Web Application for the Statistical Analysis of Continuous Glucose Monitoring Data in Epidemiological Studies

2021 ◽  
pp. 193229682098557
Author(s):  
Alysha M. De Livera ◽  
Jonathan E. Shaw ◽  
Neale Cohen ◽  
Anne Reutens ◽  
Agus Salim
Keyword(s):  
Continuous Glucose Monitoring ◽  
Web Application ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Epidemiological Studies ◽  
Interactive Software ◽  
Web Based ◽  
Software Applications ◽  
Visualization Of Data ◽  
User Friendly

Motivation: Continuous glucose monitoring (CGM) systems are an essential part of novel technology in diabetes management and care. CGM studies have become increasingly popular among researchers, healthcare professionals, and people with diabetes due to the large amount of useful information that can be collected using CGM systems. The analysis of the data from these studies for research purposes, however, remains a challenge due to the characteristics and large volume of the data. Results: Currently, there are no publicly available interactive software applications that can perform statistical analyses and visualization of data from CGM studies. With the rapidly increasing popularity of CGM studies, such an application is becoming necessary for anyone who works with these large CGM datasets, in particular for those with little background in programming or statistics. CGMStatsAnalyser is a publicly available, user-friendly, web-based application, which can be used to interactively visualize, summarize, and statistically analyze voluminous and complex CGM datasets together with the subject characteristics with ease.

CPVA: a web-based metabolomic tool for chromatographic peak visualization and annotation

2020 ◽  
Vol 36 (12) ◽  
pp. 3913-3915
Author(s):  
Hemi Luan ◽  
Xingen Jiang ◽  
Fenfen Ji ◽  
Zhangzhang Lan ◽  
Zongwei Cai ◽  
...  
Keyword(s):  
False Positive ◽  
Supplementary Information ◽  
Liquid Chromatography Mass Spectrometry ◽  
Targeted Metabolomics ◽  
Metabolomics Data ◽  
Web Based ◽  
Tremendous Amount ◽  
Chromatographic Peaks ◽  
User Friendly

Abstract Motivation Liquid chromatography–mass spectrometry-based non-targeted metabolomics is routinely performed to qualitatively and quantitatively analyze a tremendous amount of metabolite signals in complex biological samples. However, false-positive peaks in the datasets are commonly detected as metabolite signals by using many popular software, resulting in non-reliable measurement. Results To reduce false-positive calling, we developed an interactive web tool, termed CPVA, for visualization and accurate annotation of the detected peaks in non-targeted metabolomics data. We used a chromatogram-centric strategy to unfold the characteristics of chromatographic peaks through visualization of peak morphology metrics, with additional functions to annotate adducts, isotopes and contaminants. CPVA is a free, user-friendly tool to help users to identify peak background noises and contaminants, resulting in decrease of false-positive or redundant peak calling, thereby improving the data quality of non-targeted metabolomics studies. Availability and implementation The CPVA is freely available at http://cpva.eastus.cloudapp.azure.com. Source code and installation instructions are available on GitHub: https://github.com/13479776/cpva. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals PathScore: a web tool for identifying altered pathways in cancer data

2016 ◽  
Author(s):  
Stephen G. Gaffney ◽  
Jeffrey P. Townsend
Keyword(s):  
Web Application ◽  
Somatic Mutations ◽  
Supplementary Information ◽  
Web Tool ◽  
Cancer Data ◽  
Link Type ◽  
Novel Approach ◽  
Supplementary Material ◽  
User Friendly ◽  
Pathway Effect

ABSTRACTSummaryPathScore quantifies the level of enrichment of somatic mutations within curated pathways, applying a novel approach that identifies pathways enriched across patients. The application provides several user-friendly, interactive graphic interfaces for data exploration, including tools for comparing pathway effect sizes, significance, gene-set overlap and enrichment differences between projects.Availability and ImplementationWeb application available at pathscore.publichealth.yale.edu. Site implemented in Python and MySQL, with all major browsers supported. Source code available at github.com/sggaffney/pathscore with a GPLv3 [email protected] InformationAdditional documentation can be found at http://pathscore.publichealth.yale.edu/faq.

scholarly journals YeastSpotter: accurate and parameter-free web segmentation for microscopy images of yeast cells

2019 ◽  
Vol 35 (21) ◽  
pp. 4525-4527 ◽  
Author(s):  
Alex X Lu ◽  
Taraneh Zarin ◽  
Ian S Hsu ◽  
Alan M Moses
Keyword(s):  
Image Analysis ◽  
Web Application ◽  
Single Cells ◽  
Yeast Cells ◽  
Supplementary Information ◽  
Supplementary Data ◽  
User Friendly ◽  
Microscopy Images

Abstract Summary We introduce YeastSpotter, a web application for the segmentation of yeast microscopy images into single cells. YeastSpotter is user-friendly and generalizable, reducing the computational expertise required for this critical preprocessing step in many image analysis pipelines. Availability and implementation YeastSpotter is available at http://yeastspotter.csb.utoronto.ca/. Code is available at https://github.com/alexxijielu/yeast_segmentation. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals DiscoRhythm: an easy-to-use web application and R package for discovering rhythmicity

2019 ◽  
Author(s):  
Matthew Carlucci ◽  
Algimantas Kriščiūnas ◽  
Haohan Li ◽  
Povilas Gibas ◽  
Karolis Koncevičius ◽  
...  
Keyword(s):  
Web Application ◽  
Statistical Significance ◽  
R Package ◽  
Biological Data ◽  
Supplementary Information ◽  
Statistical Knowledge ◽  
Health And Disease ◽  
Phase Amplitude ◽  
Almost All ◽  
User Friendly

Abstract Motivation Biological rhythmicity is fundamental to almost all organisms on Earth and plays a key role in health and disease. Identification of oscillating signals could lead to novel biological insights, yet its investigation is impeded by the extensive computational and statistical knowledge required to perform such analysis. Results To address this issue, we present DiscoRhythm (Discovering Rhythmicity), a user-friendly application for characterizing rhythmicity in temporal biological data. DiscoRhythm is available as a web application or an R/Bioconductor package for estimating phase, amplitude, and statistical significance using four popular approaches to rhythm detection (Cosinor, JTK Cycle, ARSER, and Lomb-Scargle). We optimized these algorithms for speed, improving their execution times up to 30-fold to enable rapid analysis of -omic-scale datasets in real-time. Informative visualizations, interactive modules for quality control, dimensionality reduction, periodicity profiling, and incorporation of experimental replicates make DiscoRhythm a thorough toolkit for analyzing rhythmicity. Availability and Implementation The DiscoRhythm R package is available on Bioconductor (https://bioconductor.org/packages/DiscoRhythm), with source code available on GitHub (https://github.com/matthewcarlucci/DiscoRhythm) under a GPL-3 license. The web application is securely deployed over HTTPS (https://disco.camh.ca) and is freely available for use worldwide. Local instances of the DiscoRhythm web application can be created using the R package or by deploying the publicly available Docker container (https://hub.docker.com/r/mcarlucci/discorhythm). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals A WEB-BASED FAST AND RELIABLE TEXT CLASSIFICATION TOOL

2019 ◽  
Vol 1 ◽  
pp. 24
Author(s):  
Jānis Kapenieks
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Data Storage ◽  
Text Classification ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Web Based ◽  
Opinion Analysis ◽  
Classification Tool ◽  
User Friendly

INTRODUCTION Opinion analysis in the big data analysis context has been a hot topic in science and the business world recently. Social media has become a key data source for opinions generating a large amount of data every day providing content for further analysis. In the Big data age, unstructured data classification is one of the key tools for fast and reliable content analysis. I expect significant growth in the demand for content classification services in the nearest future. There are many online text classification tools available providing limited functionality -such as automated text classification in predefined categories and sentiment analysis based on a pre-trained machine learning algorithm. The limited functionality does not provide tools such as data mining support and/or a machine learning algorithm training interface. There are a limited number of tools available providing the whole sets of tools required for text classification, i.e. this includes all the steps starting from data mining till building a machine learning algorithm and applying it to a data stream from a social network source. My goal is to create a tool able to generate a classified text stream directly from social media with a user friendly set-up interface. METHODS AND MATERIALS The text classification tool will have a core based modular structure (each module providing certain functionality) so the system can be scaled in terms of technology and functionality. The tool will be built on open source libraries and programming languages running on a Linux OS based server. The tool will be based on three key components: frontend, backend and data storage as described below: backend: Python and Nodejs programming language with machine learning and text filtering libraries: TensorFlow, and Keras, for data storage Mysql 5.7/8 will be used, frontend will be based on web technologies built using PHP and Javascript. EXPECTED RESULTS The expected result of my work is a web-based text classification tool for opinion analysis using data streams from social media. The tool will provide a user friendly interface for data collection, algorithm selection, machine learning algorithm setup and training. Multiple text classification algorithms will be available as listed below: Linear SVM Random Forest Multinomial Naive Bayes Bernoulli Naive Bayes Ridge Regressio Perceptron Passive Aggressive Classifier Deep machine learning algorithm. System users will be able to identify the most effective algorithm for their text classification task and compare them based on their accuracy. The architecture of the text classification tool will be based on a frontend interface and backend services. The frontend interface will provide all the tools the system user will be interacting with the system. This includes setting up data collection streams from multiple social networks and allocating them to pre-specified channels based on keywords. Data from each channel can be classified and assigned to a pre-defined cluster. The tool will provide a training interface for machine learning algorithms. This text classification tool is currently in active development for a client with planned testing and implementation in April 2019.

scholarly journals Data Browser Matsch | Mazia: Web Application to access microclimatic time series of an ecological research site

2021 ◽  
Vol 7 ◽  
Author(s):  
Martin Palma ◽  
Alessandro Zandonai ◽  
Luca Cattani ◽  
Johannes Klotz ◽  
Giulio Genova ◽  
...  
Keyword(s):  
Time Series ◽  
Web Application ◽  
Scientific Data ◽  
Time Range ◽  
Ecological Research ◽  
Data Accessibility ◽  
Web Based ◽  
South Tyrol ◽  
Research Site ◽  
User Friendly

Easily accessible data is an essential requirement for scientific data analysis. The Data Browser Matsch | Mazia was designed to provide a fast and comprehensible solution to access, visualize and download the microclimatic measurements of the IT 25 LT(S)ER Match | Mazia research site in South Tyrol, Northern Italy, with the overall aim to provide straightforward data accessibility and enhance dissemination. Data Browser Matsch | Mazia is a user-friendly web-based application to visualize and download micrometeorological and biophysical time series of the Long-Term Socio-Ecological Research site Matsch | Mazia in South Tyrol, Italy. It is designed both for the general public and researchers. The Data Browser Matsch | Mazia drop-down menus allow the user to query the InfluxDB database in the backend by selecting the measurements, time range, land use and elevation. Interactive Grafana dashboards show dynamic graphs of the time series.

scholarly journals RaDMaX online: a web-based program for the determination of strain and damage profiles in irradiated crystals using X-ray diffraction

2020 ◽  
Vol 53 (2) ◽  
pp. 587-593
Author(s):  
A. Boulle ◽  
V. Mergnac
Keyword(s):  
Web Application ◽  
The Internet ◽  
Programming Environment ◽  
X Ray Diffraction ◽  
Web Browser ◽  
Web Based ◽  
X Ray ◽  
Depth Profiles ◽  
User Friendly

RaDMaX online is a major update to the previously published RaDMaX (radiation damage in materials analysed with X-ray diffraction) software [Souilah, Boulle & Debelle (2016). J. Appl. Cryst. 49, 311–316]. This program features a user-friendly interface that allows retrieval of strain and disorder depth profiles in irradiated crystals from the simulation of X-ray diffraction data recorded in symmetrical θ/2θ mode. As compared with its predecessor, RaDMaX online has been entirely rewritten in order to be able to run within a simple web browser, therefore avoiding the necessity to install any programming environment on the users' computers. The RaDMaX online web application is written in Python and developed within a Jupyter notebook implementing graphical widgets and interactive plots. RaDMaX online is free and open source and can be accessed on the internet at https://aboulle.github.io/RaDMaX-online/.

scholarly journals The Framework for Web-Based Automated Online Question Paper Generator through JEE

2018 ◽  
Vol 7 (3) ◽  
pp. 1415
Author(s):  
Vinayak Hegde ◽  
Lavanya V Rao ◽  
Shivali B S
Keyword(s):  
Web Application ◽  
Large Scale ◽  
Educational Institution ◽  
Faculty Members ◽  
Educational Institutions ◽  
Small Scale ◽  
Web Based ◽  
Educational Institute ◽  
User Friendly ◽  
Word Format

Examinations are an indispensable part of a student’s life. In the conventional mechanism, the question paper generation is time-consuming work for the faculty members of the educational institution. Every educational institute mandatorily expects exam setters to follow its own typesetting format. We have designed the automated question paper setting software to be user-friendly so that, paper setters can overcome from the typographic problem. Presently in most of the educational institutions question papers are set manually. It is time-consuming work and there may be chances of repetition of the same questions. So, in order to make the question paper generation more convenient to use, the web application is developed using Java Enterprise Edition (JEE) that can be accessed from LAN/Intranet.The application comes with the Admin Module and Teachers Module. The Admin grants access to the users by registering them. The faculty can access the system once they are registered. The faculty can enter questions in the database daily as per their free time. In this way, the question pool can be generated. The questions are approved by the chairperson and substandard questions are discarded. The question paper is then generated by selected course experts. The Fisher-Yates Shuffling algorithm used to choose questions randomly from the pool of questions from the database. Text Mining Algorithm aids in duplicity removal from the paper.  The generated question paper will be in Word Format. In our application, we assure better security, removal of duplicity, cost-effectiveness, and human intervention avoidance. It can be used by small-scale and large-scale institutions.  

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