scholarly journals BiocPkgTools: Toolkit for Mining the Bioconductor Package Ecosystem

2019 ◽  
Author(s):  
Shian Su ◽  
Vincent J. Carey ◽  
Lori Shepherd ◽  
Matthew Ritchie ◽  
Martin T. Morgan ◽  
...  
Keyword(s):  
Open Source Software ◽  
Large Scale ◽  
Biological Data ◽  
Bioconductor Package ◽  
Large Collection ◽  
End User ◽  
Graph Analytics ◽  
Standard Procedures ◽  
User Friendly ◽  
Reporting Data

AbstractMotivationThe Bioconductor project, a large collection of open source software for the comprehension of large-scale biological data, continues to grow with new packages added each week, motivating the development of software tools focused on exposing package metadata to developers and users. The resulting BiocPkgTools package facilitates access to extensive metadata in computable form covering the Bioconductor package ecosystem, facilitating downstream applications such as custom reporting, data and text mining of Bioconductor package text descriptions, graph analytics over package dependencies, and custom search approaches.ResultsThe BiocPkgTools package has been incorporated into the Bioconductor project, installs using standard procedures, and runs on any system supporting R. It provides functions to load detailed package metadata, longitudinal package download statistics, package dependencies, and Bioconductor build reports, all in “tidy data” form. BiocPkgTools can convert from tidy data structures to graph structures, enabling graphbased analytics and visualization. An end-user-friendly graphical package explorer aids in task-centric package discovery. Full documentation and example use cases are included.AvailabilityThe BiocPkgTools software and complete documentation are available from Bioconductor (https://bioconductor.org/packages/BiocPkgTools).

scholarly journals BiocPkgTools: Toolkit for mining the Bioconductor package ecosystem

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 752
Author(s):  
Shian Su ◽  
Vincent J. Carey ◽  
Lori Shepherd ◽  
Matthew Ritchie ◽  
Martin T. Morgan ◽  
...  
Keyword(s):  
Open Source Software ◽  
Large Scale ◽  
Biological Data ◽  
Bioconductor Package ◽  
End User ◽  
Graph Analytics ◽  
Standard Procedures ◽  
Bioconductor Project ◽  
User Friendly ◽  
Reporting Data

Motivation: The Bioconductor project, a large collection of open source software for the comprehension of large-scale biological data, continues to grow with new packages added each week, motivating the development of software tools focused on exposing package metadata to developers and users. The resulting BiocPkgTools package facilitates access to extensive metadata in computable form covering the Bioconductor package ecosystem, facilitating downstream applications such as custom reporting, data and text mining of Bioconductor package text descriptions, graph analytics over package dependencies, and custom search approaches. Results: The BiocPkgTools package has been incorporated into the Bioconductor project, installs using standard procedures, and runs on any system supporting R. It provides functions to load detailed package metadata, longitudinal package download statistics, package dependencies, and Bioconductor build reports, all in "tidy data" form. BiocPkgTools can convert from tidy data structures to graph structures, enabling graph-based analytics and visualization. An end-user-friendly graphical package explorer aids in task-centric package discovery. Full documentation and example use cases are included. Availability: The BiocPkgTools software and complete documentation are available from Bioconductor (https://bioconductor.org/packages/BiocPkgTools).

scholarly journals GDCRNATools: an R/Bioconductor package for integrative analysis of lncRNA, miRNA, and mRNA data in GDC

2017 ◽  
Author(s):  
Ruidong Li ◽  
Han Qu ◽  
Shibo Wang ◽  
Julong Wei ◽  
Le Zhang ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Large Scale ◽  
Genomic Data ◽  
Regulatory Mechanisms ◽  
Omics Data ◽  
Bioconductor Package ◽  
Competing Endogenous Rnas ◽  
Downstream Analysis ◽  
User Friendly ◽  
Data Commons

AbstractThe large-scale multidimensional omics data in the Genomic Data Commons (GDC) provides opportunities to investigate the crosstalk among different RNA species and their regulatory mechanisms in cancers. Easy-to-use bioinformatics pipelines are needed to facilitate such studies. We have developed a user-friendly R/Bioconductor package, named GDCRNATools, to facilitate downloading, organizing, and analyzing RNA data in GDC with an emphasis on deciphering the lncRNA-mRNA related competing endogenous RNAs (ceRNAs) regulatory network in cancers. Many widely used bioinformatics tools and databases are utilized in our package. Users can easily pack preferred downstream analysis pipelines or integrate their own pipelines into the workflow. Interactive shiny web apps built in GDCRNATools greatly improve visualization of results from the analysis.AvailabilityGDCRNATools is an R/Bioconductor package that is freely available at https://github.com/Jialab-UCR/GDCRNATools

Study of Biochemical and Clinical Markers in Steatohepatitis Related to Obesity

2018 ◽  
Vol 69 (6) ◽  
pp. 1501-1505
Author(s):  
Roxana Maria Livadariu ◽  
Radu Danila ◽  
Lidia Ionescu ◽  
Delia Ciobanu ◽  
Daniel Timofte
Keyword(s):  
Liver Disease ◽  
Liver Biopsy ◽  
Large Scale ◽  
Biological Data ◽  
Obese Patients ◽  
Clinical Markers ◽  
Mean Values ◽  
Nonalcoholic Fatty Liver ◽  
Obstructive Sleep ◽  
Increased Risk

Nonalcoholic fatty liver disease (NAFLD) is highly associated to obesity and comprises several liver diseases, from simple steatosis to steatohepatitis (NASH) with increased risk of developing progressive liver fibrosis, cirrhosis and hepatocellular carcinoma. Liver biopsy is the gold standard in diagnosing the disease, but it cannot be used in a large scale. The aim of the study was the assessment of some non-invasive clinical and biological markers in relation to the progressive forms of NAFLD. We performed a prospective study on 64 obese patients successively hospitalised for bariatric surgery in our Surgical Unit. Patients with history of alcohol consumption, chronic hepatitis B or C, other chronic liver disease or patients undergoing hepatotoxic drug use were excluded. All patients underwent liver biopsy during sleeve gastrectomy. NAFLD was present in 100% of the patients: hepatic steatosis (38%), NASH with the two forms: with fibrosis (31%) and without fibrosis (20%), cumulating 51%; 7 patients had NASH with vanished steatosis. NASH with fibrosis statistically correlated with metabolic syndrome (p = 0.036), DM II (p = 0.01) and obstructive sleep apnea (p = 0.02). Waist circumference was significantly higher in the steatohepatitis groups (both with and without fibrosis), each 10 cm increase increasing the risk of steatohepatitis (p = 0.007). The mean values of serum fibrinogen and CRP were significantly higher in patients having the progressive forms of NAFLD. Simple clinical and biological data available to the practitioner in medicine can be used to identify obese patients at high risk of NASH, aiming to direct them to specialized medical centers.

scholarly journals PRISMS-Fatigue computational framework for fatigue analysis in polycrystalline metals and alloys

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Mohammadreza Yaghoobi ◽  
Krzysztof S. Stopka ◽  
Aaditya Lakshmanan ◽  
Veera Sundararaghavan ◽  
John E. Allison ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Metals And Alloys ◽  
Analysis Tool ◽  
Computational Framework ◽  
Crystal Plasticity Finite Element ◽  
Polycrystalline Metals ◽  
Simulation Based ◽  
Open Source Framework

AbstractThe PRISMS-Fatigue open-source framework for simulation-based analysis of microstructural influences on fatigue resistance for polycrystalline metals and alloys is presented here. The framework uses the crystal plasticity finite element method as its microstructure analysis tool and provides a highly efficient, scalable, flexible, and easy-to-use ICME community platform. The PRISMS-Fatigue framework is linked to different open-source software to instantiate microstructures, compute the material response, and assess fatigue indicator parameters. The performance of PRISMS-Fatigue is benchmarked against a similar framework implemented using ABAQUS. Results indicate that the multilevel parallelism scheme of PRISMS-Fatigue is more efficient and scalable than ABAQUS for large-scale fatigue simulations. The performance and flexibility of this framework is demonstrated with various examples that assess the driving force for fatigue crack formation of microstructures with different crystallographic textures, grain morphologies, and grain numbers, and under different multiaxial strain states, strain magnitudes, and boundary conditions.

scholarly journals Sampo-UI: A full stack JavaScript framework for developing semantic portal user interfaces

Semantic Web ◽  
2021 ◽  
pp. 1-16
Author(s):  
Esko Ikkala ◽  
Eero Hyvönen ◽  
Heikki Rantala ◽  
Mikko Koho
Keyword(s):  
User Interfaces ◽  
Linked Data ◽  
State Of The Art ◽  
Software Framework ◽  
End User ◽  
Faceted Search ◽  
Software Developer ◽  
Current State ◽  
Knowledge Graphs ◽  
User Friendly

This paper presents a new software framework, Sampo-UI, for developing user interfaces for semantic portals. The goal is to provide the end-user with multiple application perspectives to Linked Data knowledge graphs, and a two-step usage cycle based on faceted search combined with ready-to-use tooling for data analysis. For the software developer, the Sampo-UI framework makes it possible to create highly customizable, user-friendly, and responsive user interfaces using current state-of-the-art JavaScript libraries and data from SPARQL endpoints, while saving substantial coding effort. Sampo-UI is published on GitHub under the open MIT License and has been utilized in several internal and external projects. The framework has been used thus far in creating six published and five forth-coming portals, mostly related to the Cultural Heritage domain, that have had tens of thousands of end-users on the Web.

scholarly journals Using Participatory Design to Design an eHealth Well-Being Program

2021 ◽  
Vol 18 (14) ◽  
pp. 7250
Author(s):  
Yannick van Hierden ◽  
Timo Dietrich ◽  
Sharyn Rundle-Thiele
Keyword(s):  
Best Practices ◽  
Health Professionals ◽  
Participatory Design ◽  
Online Community ◽  
Well Being ◽  
Proof Of Concept ◽  
End User ◽  
Ehealth Intervention ◽  
Pilot Intervention ◽  
User Friendly

In recent years, the relevance of eHealth interventions has become increasingly evident. However, a sequential procedural application to cocreating eHealth interventions is currently lacking. This paper demonstrates the implementation of a participatory design (PD) process to inform the design of an eHealth intervention aiming to enhance well-being. PD sessions were conducted with 57 people across four sessions. Within PD sessions participants experienced prototype activities, provided feedback and designed program interventions. A 5-week eHealth well-being intervention focusing on lifestyle, habits, physical activity, and meditation was proposed. The program is suggested to be delivered through online workshops and online community interaction. A five-step PD process emerged; namely, (1) collecting best practices, (2) participatory discovery, (3) initial proof-of-concept, (4) participatory prototyping, and (5) pilot intervention proof-of-concept finalisation. Health professionals, behaviour change practitioners and program planners can adopt this process to ensure end-user cocreation using the five-step process. The five-step PD process may help to create user-friendly programs.

scholarly journals Graph Convolutional Network for Drug Response Prediction Using Gene Expression Data

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 772
Author(s):  
Seonghun Kim ◽  
Seockhun Bae ◽  
Yinhua Piao ◽  
Kyuri Jo
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Large Scale ◽  
Drug Response ◽  
Response Prediction ◽  
Biological Data ◽  
Expression Data ◽  
Convolutional Network ◽  
Essential Information ◽  
Protein Protein Interaction

Genomic profiles of cancer patients such as gene expression have become a major source to predict responses to drugs in the era of personalized medicine. As large-scale drug screening data with cancer cell lines are available, a number of computational methods have been developed for drug response prediction. However, few methods incorporate both gene expression data and the biological network, which can harbor essential information about the underlying process of the drug response. We proposed an analysis framework called DrugGCN for prediction of Drug response using a Graph Convolutional Network (GCN). DrugGCN first generates a gene graph by combining a Protein-Protein Interaction (PPI) network and gene expression data with feature selection of drug-related genes, and the GCN model detects the local features such as subnetworks of genes that contribute to the drug response by localized filtering. We demonstrated the effectiveness of DrugGCN using biological data showing its high prediction accuracy among the competing methods.

Microcomputer Simulations of Presidential Elections

1983 ◽  
Vol 38 ◽  
pp. 20-20
Author(s):  
Robert S. Ross
Keyword(s):  
Social Sciences ◽  
Large Scale ◽  
Role Playing ◽  
Science Students ◽  
Instructional Programs ◽  
Santa Barbara ◽  
Large Scale Systems ◽  
The Social ◽  
User Friendly ◽  
Machine Interaction

Simulations have been an important adjunct to instructional programs for some time. These have ranged from games, or role playing exercises, such as SIMSOC or Internation Simulation, to student-machine interaction, such as the inter-school simulation run out of University of California, Santa Barbara in the early 70's, to the all machine activities found in some of the early SETUPS. Having social science students use the mainframe computer, however, always posed problems: it definitely was not user-friendly and most instructors had little if any training or interest in the use of large scale systems.The wide-spread use of the micro computer is not only revolutionizing areas traditionally relying upon the computer, but is going to have an impact on the social sciences as well.

scholarly journals Current Advances in Robotics for Head and Neck Surgery—A Systematic Review

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1398
Author(s):  
Felix Boehm ◽  
Rene Graesslin ◽  
Marie-Nicole Theodoraki ◽  
Leon Schild ◽  
Jens Greve ◽  
...  
Keyword(s):  
Systematic Review ◽  
Head And Neck ◽  
Large Scale ◽  
Case Series ◽  
Clinical Effectiveness ◽  
Neck Surgery ◽  
Head And Neck Surgery ◽  
Daily Routine ◽  
Surgical Robots ◽  
Standard Procedures

Background. In the past few years, surgical robots have recently entered the medical field, particularly in urology, gynecology, and general surgery. However, the clinical effectiveness and safety of robot-assisted surgery (RAS) in the field of head and neck surgery has not been clearly established. In this review, we evaluate to what extent RAS can potentially be applied in head and neck surgery, in which fields it is already daily routine and what advantages can be seen in comparison to conventional surgery. Data sources. For this purpose, we conducted a systematic review of trials published between 2000 and 2021, as well as currently ongoing trials registered in clinicaltrials.gov. The results were structured according to anatomical regions, for the topics “Costs,” “current clinical trials,” and “robotic research” we added separate sections for the sake of clarity. Results. Our findings show a lack of large-scale systematic randomized trials on the use of robots in head and neck surgery. Most studies include small case series or lack a control arm which enables a comparison with established standard procedures. Conclusion. The question of financial reimbursement is still not answered and the systems on the market still require some specific improvements for the use in head and neck surgery.

scholarly journals A Study of Quality Indicator Model of Large-Scale Open Source Software Projects for Adoption Decision-making

2020 ◽  
Vol 176 ◽  
pp. 3665-3672
Author(s):  
Shinji Akatsu ◽  
Ayako Masuda ◽  
Tsuyoshi Shida ◽  
Kazuhiko Tsuda
Keyword(s):  
Decision Making ◽  
Open Source ◽  
Open Source Software ◽  
Quality Indicator ◽  
Large Scale ◽  
Software Projects ◽  
Adoption Decision ◽  
Indicator Model
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