scholarly journals Tribe: The collaborative platform for reproducible web-based analysis of gene sets

2016 ◽  
Author(s):  
René A. Zelaya ◽  
Aaron K. Wong ◽  
Alex T. Frase ◽  
Marylyn D. Ritchie ◽  
Casey S. Greene
Keyword(s):  
Open Source ◽  
Web Interface ◽  
Web Based ◽  
Gene Set ◽  
Collaborative Editing ◽  
Gene Sets ◽  
Collaborative Platform ◽  
Set Up ◽  
User Friendly ◽  
Multi Server

AbstractBackgroundThe adoption of new bioinformatics webservers provides biological researchers with new analytical opportunities but also raises workflow challenges. These challenges include sharing collections of genes with collaborators, translating gene identifiers to the most appropriate nomenclature for each server, tracking these collections across multiple analysis tools and webservers, and maintaining effective records of the genes used in each analysis.DescriptionIn this paper, we present the Tribe webserver (available at https://tribe.greenelab.com), which addresses these challenges in order to make multi-server workflows seamless and reproducible. This allows users to create analysis pipelines that use their own sets of genes in combinations of specialized data mining webservers and tools while seamlessly maintaining gene set version control. Tribe’s web interface facilitates collaborative editing: users can share with collaborators, who can then view, download, and edit these collections. Tribe’s fully-featured API allows users to interact with Tribe programmatically if desired. Tribe implements the OAuth 2.0 standard as well as gene identifier mapping, which facilitates its integration into existing servers. Access to Tribe’s resources is facilitated by an easy-to-install Python application called tribe-client. We provide Tribe and tribe-client under a permissive open-source license to encourage others to download the source code and set up a local instance or to extend its capabilities.ConclusionsThe Tribe webserver addresses challenges that have made reproducible multi-webserver workflows difficult to implement until now. It is open source, has a user-friendly web interface, and provides a means for researchers to perform reproducible gene set based analyses seamlessly across webservers and command line tools.

scholarly journals Short-term adoption rates for a web-based portal within the intranet of a hospital information system

2019 ◽  
Vol 26 (1) ◽  
pp. e100004 ◽  
Author(s):  
Athanasios Kotoulas ◽  
Ioannis Stratis ◽  
Theodoros Goumenidis ◽  
George Lambrou ◽  
Dimitrios - Dionysios Koutsouris
Keyword(s):  
Open Source ◽  
Resistance To Change ◽  
Content Management ◽  
Healthcare Management ◽  
Short Term ◽  
Web Based ◽  
Average Growth ◽  
Greek Hospital ◽  
Set Up ◽  
Free Open Source

ObjectiveAn intranet portal that combines cost-free, open-source software technology with easy set-up features can be beneficial for daily hospital processes. We describe the short-term adoption rates of a costless content management system (CMS) in the intranet of a tertiary Greek hospital.DesignDashboard statistics of our CMS platform were the implementation assessment of our system.ResultsIn a period of 10 months of running the software, the results indicate the employees overcame ‘Resistance to Change’ status. The average growth rate of end users who exploit the portal services is calculated as 2.73 every 3.3 months.ConclusionWe found our intranet web-based portal to be acceptable and helpful so far. Exploitation of an open-source CMS within the hospital intranet can influence healthcare management and the employees’ way of working as well.

scholarly journals MESPEUS: a database of the geometry of metal sites in proteins

2008 ◽  
Vol 41 (5) ◽  
pp. 963-968 ◽  
Author(s):  
K. Hsin ◽  
Y. Sheng ◽  
M. M. Harding ◽  
P. Taylor ◽  
M. D. Walkinshaw
Keyword(s):  
Protein Molecule ◽  
Data Bank ◽  
Web Interface ◽  
Coordination Numbers ◽  
Data Resolution ◽  
Metal Metal ◽  
Set Up ◽  
Stored Information ◽  
Interacting Atoms ◽  
User Friendly

A database with details of the geometry of metal sites in proteins has been set up. The data are derived from metalloprotein structures that are in the Protein Data Bank [PDB; Berman, Henrick, Nakamura & Markley (2006).Nucleic Acids Res.35, D301–D303] and have been determined at 2.5 Å resolution or better. The database contains all contacts within the crystal asymmetric unit considered to be chemical bonds to any of the metals Na, Mg, K, Ca, Mn, Fe, Co, Ni, Cu or Zn. The stored information includes PDB code, crystal data, resolution of structure determination, refinement program andRfactor, protein class (from PDB header), contact distances, atom names of metal and interacting atoms as they appear in the PDB, site occupancies,Bvalues, coordination numbers, information on coordination shapes, and metal–metal distances. This may be accessed by SQL queries, or by a user-friendly web interface which searches for contacts between specified types of atoms [for example Ca and carboxylate O of aspartate, Co and imidazole Nδ of histidine] or which delivers details of all the metal sites in a specified protein. The web interface allows graphical display of the metal site, on its own or within the whole protein molecule, and may be accessed at http://eduliss.bch.ed.ac.uk/MESPEUS/. Some applications are briefly described, including a study of the characteristics of Mg sites that bind adenosine triphosphate, the derivation of an average Mg—Ophosphatedistance and some problems that arise when average bond distances with high precision are required.

scholarly journals GenSensor Suite: A Web-Based Tool for the Analysis of Gene and Protein Interactions, Pathways, and Regulation

2011 ◽  
Vol 2011 ◽  
pp. 1-7 ◽  
Author(s):  
Mark Gosink ◽  
Sawsan Khuri ◽  
Camilo Valdes ◽  
Zhijie Jiang ◽  
Nicholas F. Tsinoremas
Keyword(s):  
Protein Interactions ◽  
Single Gene ◽  
Gene List ◽  
Input List ◽  
Web Based ◽  
Common Gene ◽  
Gene Set ◽  
Web Tools ◽  
Gene Sets

The GenSensor Suite consists of four web tools for elucidating relationships among genes and proteins. GenPath results show which biochemical, regulatory, or other gene set categories are over- or under-represented in an input list compared to a background list. All common gene sets are available for searching in GenPath, plus some specialized sets. Users can add custom background lists. GenInteract builds an interaction gene list from a single gene input and then analyzes this in GenPath. GenPubMed uses a PubMed query to identify a list of PubMed IDs, from which a gene list is extracted and queried in GenPath. GenViewer allows the user to query one gene set against another in GenPath. GenPath results are presented with relevant P- and q-values in an uncluttered, fully linked, and integrated table. Users can easily copy this table and paste it directly into a spreadsheet or document.

scholarly journals Developing a Coupling Model System of Global Rainfall Data and Open-Source Model for Water Forecast in Poorly Gauged Basins

2019 ◽  
Vol 3 (1) ◽  
pp. 355 ◽  
Author(s):  
Duong Du Bui ◽  
Duc Minh Tran ◽  
Huong Thi Vu ◽  
Nuong Thi Bui
Keyword(s):  
Open Source ◽  
Input Data ◽  
Water Security ◽  
Coupling Model ◽  
Source Model ◽  
Rainfall Data ◽  
Creative Commons ◽  
Set Up ◽  
User Friendly

Water security is under severe pressures from human interventions and climate change in all over the world and improved water forecast is essential for water management. HYPE is a semi-distributed hydrographic model, running on Windows or Linux operating systems. The code of the model is written by the Fortran programming language and open source as Lesser GNU Public License. HYPE has been becoming a widely used tool in the forecasting of transboundary flows. However, the application of HYPE encounters many difficulties in processing input data and serving the construction, calibration, and validation of the model. This article introduces the development of the V-HYPE tool that helps a couple of global rainfall data and HYPE model for operational use. V-HYPE allows developing a user-friendly interface and setting parameters of the HYPE model as well as evaluating errors and transforming and visually displaying the results of the model. Besides, the V-HYPE has the ability to show related maps (i.e. sub-basins, river network, lake, and dams, etc), set up input data, automatically download global rainfall data, and visually display results on WebGIS. V-HYPE also can generate bulletins supporting for operational water resources warning and forecasting works in Vietnam. The utilities of this tool are demonstrated in the case study of Serepok river basin.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

scholarly journals PhenoExam: an R package and Web application for the examination of phenotypes linked to genes and gene sets

2021 ◽  
Author(s):  
Alejandro Cisterna García ◽  
Aurora González-Vidal ◽  
Daniel Ruiz Villa ◽  
Jordi Ortiz Murillo ◽  
Alicia Gómez-Pascual ◽  
...  
Keyword(s):  
Web Application ◽  
Enrichment Analysis ◽  
R Package ◽  
Web Interface ◽  
Gene Set ◽  
New Genes ◽  
Gene Sets ◽  
Phenotype Analysis ◽  
New Gene ◽  
Early Onset Parkinson’S Disease

Gene set based phenotype enrichment analysis (detecting phenotypic terms that emerge as significant in a set of genes) can improve the rate of genetic diagnoses amongst other research purposes. To facilitate diverse phenotype analysis, we developed PhenoExam, a freely available R package for tool developers and a web interface for users, which performs: (1) phenotype and disease enrichment analysis on a gene set; (2) measures statistically significant phenotype similarities between gene sets and (3) detects significant differential phenotypes or disease terms across different databases. PhenoExam achieves these tasks by integrating databases or resources such as the HPO, MGD, CRISPRbrain, CTD, ClinGen, CGI, OrphaNET, UniProt, PsyGeNET, and Genomics England Panel App. PhenoExam accepts both human and mouse genes as input. We developed PhenoExam to assist a variety of users, including clinicians, computational biologists and geneticists. It can be used to support the validation of new gene-to-disease discoveries, and in the detection of differential phenotypes between two gene sets (a phenotype linked to one of the gene set but no to the other) that are useful for differential diagnosis and to improve genetic panels. We validated PhenoExam performance through simulations and its application to real cases. We demonstrate that PhenoExam is effective in distinguishing gene sets or Mendelian diseases with very similar phenotypes through projecting the disease-causing genes into their annotation-based phenotypic spaces. We also tested the tool with early onset Parkinson's disease and dystonia genes, to show phenotype-level similarities but also potentially interesting differences. More specifically, we used PhenoExam to validate computationally predicted new genes potentially associated with epilepsy. Therefore, PhenoExam effectively discovers links between phenotypic terms across annotation databases through effective integration. The R package is available at https://github.com/alexcis95/PhenoExam and the Web tool is accessible at https://snca.atica.um.es/PhenoExamWeb/.

scholarly journals MOSGA: Modular Open-Source Genome Annotator

2020 ◽  
Author(s):  
Roman Martin ◽  
Thomas Hackl ◽  
Georges Hattab ◽  
Matthias G Fischer ◽  
Dominik Heider
Keyword(s):  
Open Source ◽  
Source Code ◽  
Supplementary Information ◽  
Web Interface ◽  
Fully Integrated ◽  
Sequencing Technologies ◽  
A Genome ◽  
Wide Range ◽  
User Friendly ◽  
Eukaryotic Genomes

Abstract Motivation The generation of high-quality assemblies, even for large eukaryotic genomes, has become a routine task for many biologists thanks to recent advances in sequencing technologies. However, the annotation of these assemblies—a crucial step toward unlocking the biology of the organism of interest—has remained a complex challenge that often requires advanced bioinformatics expertise. Results Here, we present MOSGA (Modular Open-Source Genome Annotator), a genome annotation framework for eukaryotic genomes with a user-friendly web-interface that generates and integrates annotations from various tools. The aggregated results can be analyzed with a fully integrated genome browser and are provided in a format ready for submission to NCBI. MOSGA is built on a portable, customizable and easily extendible Snakemake backend, and thus, can be tailored to a wide range of users and projects. Availability and implementation We provide MOSGA as a web service at https://mosga.mathematik.uni-marburg.de and as a docker container at registry.gitlab.com/mosga/mosga: latest. Source code can be found at https://gitlab.com/mosga/mosga Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

Integrated Smart Home Model

2022 ◽  
Vol 17 (3) ◽  
pp. 1-14
Author(s):  
Nurshahrily Idura Ramli ◽  
Mohd Izani Mohamed Rawi ◽  
Fatin Nur Nabila Rebuan
Keyword(s):  
Industry 4.0 ◽  
Smart Home ◽  
Academic Programs ◽  
Raspberry Pi ◽  
Web Interface ◽  
Web Based ◽  
Learning Platform ◽  
Hands On ◽  
Hands On Learning ◽  
Set Up

Today, in the realm of Industry 4.0, vastly diverse Internet of Things (IoT) technology are integrated everywhere, not to mention included in academic programs in schools and universities. Domain ratio of the final year projects in Universiti Teknologi Mara exposes a staggering hype in IoT as compared to other domains despite not having IoT included in any of the courses. Meanwhile, to fulfill the needs of the student in exploring this technology, an integrated IoT learning platform is developed. It integrates an IoT smart home model and a web-based interface as a learning platform to inspire hands-on learning for the students. The raspberry pi, motion sensor, analog gas sensor, atmospheric sensor, ultrasonic proximity sensor, and rain detector sensor are integrated together in a Lego-built smart home model where its connectivity and readings are displayed in a simple web interface to enable and inspire learning. A manual to set up the entire model is also prepared as a guide for students to set up and further explore the functionalities and operabilities of “things”.

scholarly journals Comparing tuberculosis gene signatures in malnourished individuals using the TBSignatureProfiler

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
W. Evan Johnson ◽  
Aubrey Odom ◽  
Chelsie Cintron ◽  
Mutharaj Muthaiah ◽  
Selby Knudsen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Area Under The Curve ◽  
Severe Malnutrition ◽  
Gene Set ◽  
Gene Sets ◽  
Z Scores ◽  
Latent Tb ◽  
Latent Tb Infection ◽  
User Friendly

Abstract Background Gene expression signatures have been used as biomarkers of tuberculosis (TB) risk and outcomes. Platforms are needed to simplify access to these signatures and determine their validity in the setting of comorbidities. We developed a computational profiling platform of TB signature gene sets and characterized the diagnostic ability of existing signature gene sets to differentiate active TB from LTBI in the setting of malnutrition. Methods We curated 45 existing TB-related signature gene sets and developed our TBSignatureProfiler software toolkit that estimates gene set activity using multiple enrichment methods and allows visualization of single- and multi-pathway results. The TBSignatureProfiler software is available through Bioconductor and on GitHub. For evaluation in malnutrition, we used whole blood gene expression profiling from 23 severely malnourished Indian individuals with TB and 15 severely malnourished household contacts with latent TB infection (LTBI). Severe malnutrition was defined as body mass index (BMI) < 16 kg/m2 in adults and based on weight-for-height Z scores in children < 18 years. Gene expression was measured using RNA-sequencing. Results The comparison and visualization functions from the TBSignatureProfiler showed that TB gene sets performed well in malnourished individuals; 40 gene sets had statistically significant discriminative power for differentiating TB from LTBI, with area under the curve ranging from 0.662–0.989. Three gene sets were not significantly predictive. Conclusion Our TBSignatureProfiler is a highly effective and user-friendly platform for applying and comparing published TB signature gene sets. Using this platform, we found that existing gene sets for TB function effectively in the setting of malnutrition, although differences in gene set applicability exist. RNA-sequencing gene sets should consider comorbidities and potential effects on diagnostic performance.

scholarly journals A repository of web-based bioinformatics resources developed in India

2020 ◽  
Author(s):  
Abhishek Agarwal ◽  
Piyush Agrawal ◽  
Aditi Sharma ◽  
Vinod Kumar ◽  
Chirag Mugdal ◽  
...  
Keyword(s):  
Scientific Community ◽  
Biological Databases ◽  
Web Interface ◽  
Web Based ◽  
Link Type ◽  
Complete Detail ◽  
User Friendly

AbstractIndiaBioDb (https://webs.iiitd.edu.in/raghava/indiabiodb/) is a manually curated comprehensive repository of bioinformatics resources developed and maintained by Indian researchers. This repository maintains information about 543 freely accessible functional resources that include around 258 biological databases. Each entry provides a complete detail about a resource that includes the name of resources, web link, detail of publication, information about the corresponding author, name of institute, type of resource. A user-friendly searching module has been integrated, which allows users to search our repository on any field. In order to retrieve categorized information, we integrate the browsing facility in this repository. This database can be utilized for extracting the useful information regarding the present scenario of bioinformatics inclusive of all research labs funded by government and private bodies of India. In addition to web interface, we also developed mobile to facilitate the scientific community.

scholarly journals The COMBAT-TB Workbench: Making powerful M. tuberculosis bioinformatics accessible

2021 ◽  
Author(s):  
Peter van Heusden ◽  
Ziphozahe Mashologu ◽  
Thoba Lose ◽  
Robin Warren ◽  
Alan Christoffels
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Software Components ◽  
Web Interface ◽  
Sample Analysis ◽  
Web Based ◽  
Workflow Execution ◽  
The Galaxy ◽  
User Friendly ◽  
Management Capabilities ◽  
Bioinformatics Workflow

Whole Genome Sequencing (WGS) is a powerful method for detecting drug resistance, genetic diversity and transmission dynamics of Mycobacterium tuberculosis. Implementation of WGS in public health microbiology laboratories is impeded by a lack of user-friendly, automated and semi-automated pipelines. We present the COMBAT-TB workbench, a modular, easy to install application that provides a web based environment for Mycobacterium tuberculosis bioinformatics. The COMBAT-TB Workbench is built using two main software components: the IRIDA Platform for its web-based user interface and data management capabilities and the Galaxy bioinformatics workflow platform for workflow execution. These components are combined into a single easy to install application using Docker container technology. We implemented two workflows, for M. tuberculosis sample analysis and phylogeny, in Galaxy. Building our workflows involved updating some Galaxy tools (Trimmomatic, snippy and snp-sites) and writing new Galaxy tools (snp-dists, TB-Profiler, tb_variant_filter and TB Variant Report). The irida-wf-ga2xml tool was updated to be able to work with recent versions of Galaxy and was further developed into IRIDA plugins for both workflows. In the case of the M. tuberculosis sample analysis an interface was added to update the metadata stored for each sequence sample with results gleaned from the Galaxy workflow output. Data can be loaded into the COMBAT-TB Workbench via the web interface or via the command line IRIDA uploader tool. The COMBAT-TB Workbench application deploys IRIDA, the COMBAT-TB IRIDA plugins, the MariaDB database and Galaxy using Docker containers (https://github.com/COMBAT-TB/irida-galaxy-deploy).

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