Pharmacomicrobiomics informs clinical pharmacogenomics

2019 ◽  
Vol 20 (10) ◽  
pp. 731-739 ◽  
Author(s):  
Theodora Katsila ◽  
Angeliki Balasopoulou ◽  
Ioanna Tsagaraki ◽  
George P Patrinos
Keyword(s):  
Disease Management ◽  
Drug Response ◽  
Open Science ◽  
Patient Stratification ◽  
Contextual Data ◽  
Data Sparsity ◽  
Knowledge Growth ◽  
Query System ◽  
User Friendly ◽  
Drug Networks

Aim: Microbiota–host–xenobiotics interactions in humans become of prime interest when clinical pharmacogenomics is to be implemented. Despite the advent of technology, information still needs to be translated into knowledge for optimum patient stratification and disease management. Material & methods: Herein, we mined metagenomic, pharmacometagenomic and pharmacomicrobiomic datasets to map microbiota–host–drugs networks. Results: Datasets were multifaceted and voluminous. Interoperability, data sparsity and scarcity remain a challenge. Mapping microbiota–host–drugs networks allowed the prediction of drug response/toxicity and modulation of the microbiota–host–drugs interplay. Conclusion: Our approach triangulated microbiota, host and drug networks revealing the need for contextual data and open science via microattribution to accelerate knowledge growth. Our findings may serve as a data storehouse for a user-friendly query system, coupled with databanks and databases.

scholarly journals Integrated open-source software for multiscale electrophysiology

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Konstantinos Nasiotis ◽  
Martin Cousineau ◽  
François Tadel ◽  
Adrien Peyrache ◽  
Richard M. Leahy ◽  
...  
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Analysis Data ◽  
Open Science ◽  
Dense Array ◽  
Unrestricted Access ◽  
Research Transparency ◽  
Programming Skills ◽  
User Friendly

Abstract The methods for electrophysiology in neuroscience have evolved tremendously over the recent years with a growing emphasis on dense-array signal recordings. Such increased complexity and augmented wealth in the volume of data recorded, have not been accompanied by efforts to streamline and facilitate access to processing methods, which too are susceptible to grow in sophistication. Moreover, unsuccessful attempts to reproduce peer-reviewed publications indicate a problem of transparency in science. This growing problem could be tackled by unrestricted access to methods that promote research transparency and data sharing, ensuring the reproducibility of published results. Here, we provide a free, extensive, open-source software that provides data-analysis, data-management and multi-modality integration solutions for invasive neurophysiology. Users can perform their entire analysis through a user-friendly environment without the need of programming skills, in a tractable (logged) way. This work contributes to open-science, analysis standardization, transparency and reproducibility in invasive neurophysiology.

scholarly journals ‘More constricting than inspiring’ — GPs find chronic care programmes of limited clinical utility. A qualitative study

BJGP Open ◽  
2018 ◽  
Vol 2 (2) ◽  
pp. bjgpopen18X101591 ◽  
Author(s):  
Mads Aage Toft Kristensen ◽  
Tina Drud Due ◽  
Bibi Hølge-Hazelton ◽  
Ann Dorrit Guassora ◽  
Frans Boch Waldorff
Keyword(s):  
Disease Management ◽  
Qualitative Study ◽  
Chronic Conditions ◽  
Self Care ◽  
Multiple Chronic Conditions ◽  
Patient Stratification ◽  
Complex Chronic Conditions ◽  
Healthcare Needs ◽  
Clinical Applicability ◽  
Disease Management Programmes

BackgroundAs in other countries, Danish health authorities have introduced disease management programmes (DMPs) to improve care quality. These contain clinical practice guidelines (CPGs) and guidelines for patient stratification based on doctors’ assessments of disease severity and self-care. However, these programmes are challenged when patients have complex chronic conditions.AimTo explore how GPs experience the clinical applicability of disease management programmes for patients with multiple chronic conditions and lowered self-care ability.Design & settingA qualitative study from general practice, conducted in rural areas of Denmark with economically disadvantaged populations.MethodData were collected through case-based, semi-structured interviews with 12 GPs. The principles of systematic text condensation were used in the analysis.ResultsGPs found DMPs inadequate, particularly for patients with multiple conditions and lowered self-care ability. Their experience was that adhering to multiple programmes’ CPGs resulted in too much medication, conflicting treatments, an overload of appointments, and fragmented health care. They disregarded stratifying according to guidelines because they deemed stratification criteria to reflect neither patients’ need for self-care support, nor flexible referral options to hospitals and municipalities. Therefore, GPs were often solely responsible for treatment of patients with very complex chronic conditions.ConclusionGPs found DMPs to be of limited clinical applicability due to challenges related to CPGs, patient stratification, and lack of adequate health services to support patients with complex healthcare needs. To increase the benefits of these programmes, they should be more flexible, and adjusted to the needs of patients with multiple chronic conditions and lowered self-care ability.

scholarly journals Pharmosome: an integrative and collective database for exploration and analysis of single nucleotide polymorphisms associated with disease

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 14 ◽  
Author(s):  
Peter T. Habib ◽  
Alsamman M. Alsamman ◽  
Sameh E. Hassanein ◽  
Kerolos M. Yousef ◽  
Aladdin Hamwieh
Keyword(s):  
Phylogenetic Trees ◽  
Drug Response ◽  
Nucleotide Polymorphisms ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Web Based ◽  
Consensus Sequences ◽  
Python Programming ◽  
User Friendly ◽  
To Receive

Current single nucleotide polymorphism (SNP) databases are limited to a narrow set of SNPs, which has led to a lack of interactivity between different databases, limited tools to analyze and manipulate the already existing data, and complexity in the graphical user interface. Here we introduce Pharmosome, a web-based, user-friendly and collective database for more than 30,000 human disease-related SNPs, with dynamic pipelines to explore SNPs associated with disease development, drug response and the pathways shared between different genes related to these SNPs. Pharmosome implements several tools to design primers to detect SNPs in large genomes and facilitates analysis of different SNPs to determine relationships between them by aligning sequences, constructing phylogenetic trees, and providing consensus sequences illustrating the connections between SNPs. Pharmosome was written in the Python programming language using the Django web framework in combination with HTML, CSS, and JavaScript to receive user inputs, and process and export the sorted result to the interface. Pharmosome is available from: https://pharmosome.herokuapp.com/.

scholarly journals A Synergetic R-Shiny Portal for Modeling and Tracking of COVID-19 Data

2021 ◽  
Vol 8 ◽  
Author(s):  
Mahdi Salehi ◽  
Mohammad Arashi ◽  
Andriette Bekker ◽  
Johan Ferreira ◽  
Ding-Geng Chen ◽  
...  
Keyword(s):  
Real Time ◽  
Growth Models ◽  
Open Science ◽  
R Software ◽  
Statistical Application ◽  
R Shiny ◽  
Trusted Data ◽  
User Friendly ◽  
Latent Responses ◽  
High Sense

The purpose of this paper is to introduce a useful online interactive dashboard (https://mahdisalehi.shinyapps.io/Covid19Dashboard/) that visualize and follow confirmed cases of COVID-19 in real-time. The dashboard was made publicly available on 6 April 2020 to illustrate the counts of confirmed cases, deaths, and recoveries of COVID-19 at the level of country or continent. This dashboard is intended as a user-friendly dashboard for researchers as well as the general public to track the COVID-19 pandemic, and is generated from trusted data sources and built in open-source R software (Shiny in particular); ensuring a high sense of transparency and reproducibility. The R Shiny framework serves as a platform for visualization and analysis of the data, as well as an advance to capitalize on existing data curation to support and enable open science. Coded analysis here includes logistic and Gompertz growth models, as two mathematical tools for predicting the future of the COVID-19 pandemic, as well as the Moran's index metric, which gives a spatial perspective via heat maps that may assist in the identification of latent responses and behavioral patterns. This analysis provides real-time statistical application aiming to make sense to academic- and public consumers of the large amount of data that is being accumulated due to the COVID-19 pandemic.

174 Combination of molecular and drug response data in patient-derived xenografts to assist patient stratification

2014 ◽  
Vol 50 ◽  
pp. 58
Author(s):  
S. Cairo ◽  
O. Déas ◽  
A. Beurdeley ◽  
V. Yvonnet ◽  
M.F. Poupon ◽  
...  
Keyword(s):  
Drug Response ◽  
Patient Stratification ◽  
Response Data

scholarly journals A practical guide for transparency in psychological science

2018 ◽  
Author(s):  
Olivier Klein ◽  
Tom Elis Hardwicke ◽  
Frederik Aust ◽  
Johannes Breuer ◽  
Henrik Danielsson ◽  
...  
Keyword(s):  
Management Practices ◽  
Open Science ◽  
Research Management ◽  
Reproducible Research ◽  
Research Practices ◽  
Psychological Science ◽  
Practical Guide ◽  
Study Protocols ◽  
User Friendly ◽  
Incremental Step

The credibility of scientific claims depends upon the transparency of the research products upon which they are based (e.g., study protocols, data, materials, and analysis scripts). As psychology navigates a period of unprecedented introspection, user-friendly tools and services that support open science have flourished. There has never been a better time to embrace transparent research practices. However, the plethora of decisions and choices involved can be bewildering. Here we provide a practical guide to help researchers navigate the process of preparing and sharing the products of their research. Being an open scientist means adopting a few straightforward research management practices, which lead to less error prone, reproducible research workflows. Further, this adoption can be piecemeal – each incremental step towards complete transparency adds positive value. Transparent research practices not only improve the efficiency of individual researchers, they enhance the credibility of the knowledge generated by the scientific community.

scholarly journals Pensoft’s ARPHA Publishing Platform top innovations in OA publishing as demonstrated by Subterranean Biology

2018 ◽  
Vol 1 ◽  
Author(s):  
Pavel Stoev
Keyword(s):  
Peer Review ◽  
Open Science ◽  
Research Articles ◽  
Web Based ◽  
Research Cycle ◽  
Research Objects ◽  
User Friendly ◽  
Publication Workflow ◽  
Text And Data Mining ◽  
Machine Readability

There are three key challenges that need to be addressed by journal publishers nowadays: increasing machine-readability and semantic enrichment of the published content to allow text and data mining, aggregation and re-use; adopting open science principles to expand from publication of mainly research articles to all research objects through the research cycle, and facilitating all of this to authors, reviewers and editors through novel and user-friendly technological solutions. increasing machine-readability and semantic enrichment of the published content to allow text and data mining, aggregation and re-use; adopting open science principles to expand from publication of mainly research articles to all research objects through the research cycle, and facilitating all of this to authors, reviewers and editors through novel and user-friendly technological solutions. ARPHA stands for: Authoring, Reviewing, Publishing, Hosting and Archiving, all in one place. ARPHA is the first publishing platform to support the full life cycle of a manuscript within a single online collaborative environment. The platform consists of two interconnected but independently functioning journal publishing workflows: ARPHA-XML: Entirely XML- and Web-based, collaborative authoring, peer review and publication workflow; ARPHA-DOC: Document-based submission (PDF, or text files), peer review and publication workflow. ARPHA-XML: Entirely XML- and Web-based, collaborative authoring, peer review and publication workflow; ARPHA-DOC: Document-based submission (PDF, or text files), peer review and publication workflow. A full list of services provided by ARPHA is available at: http://arphahub.com/about/services Furthermore, Pensoft has been heavily investing in the technological advancement of its journals. The most significant technologies implemented by Pensoft as demonstrated also by the journal Subterranean Biology in the recent years are: Automatic registrations of reviews at Publons - Publons helps reviewers and editors get recognition for every review they make for the journal; Dimensions - powerful tracker of citations, which provides ranking of given research in a given field; Scopus CiteScore Metrics - interactive tool providing information on journal’s performance; Еxport of published figures & supplementary materials to Biodiversity Literature Repository at ZENODO - increases visibility and traceability of article and sub-article elements; Hypothes.is - tool allowing annotations on selected texts from the published article. Automatic registrations of reviews at Publons - Publons helps reviewers and editors get recognition for every review they make for the journal; Dimensions - powerful tracker of citations, which provides ranking of given research in a given field; Scopus CiteScore Metrics - interactive tool providing information on journal’s performance; Еxport of published figures & supplementary materials to Biodiversity Literature Repository at ZENODO - increases visibility and traceability of article and sub-article elements; Hypothes.is - tool allowing annotations on selected texts from the published article.

scholarly journals Structural Biology in the Clouds: The WeNMR-EOSC Ecosystem

2021 ◽  
Vol 8 ◽  
Author(s):  
Rodrigo V. Honorato ◽  
Panagiotis I. Koukos ◽  
Brian Jiménez-García ◽  
Andrei Tsaregorodtsev ◽  
Marco Verlato ◽  
...  
Keyword(s):  
Structural Biology ◽  
Dynamic Properties ◽  
Three Dimensional ◽  
Open Science ◽  
Biological Macromolecules ◽  
Web Based ◽  
Cellular Processes ◽  
User Friendly ◽  
Insight Into ◽  
Gaining Insight

Structural biology aims at characterizing the structural and dynamic properties of biological macromolecules at atomic details. Gaining insight into three dimensional structures of biomolecules and their interactions is critical for understanding the vast majority of cellular processes, with direct applications in health and food sciences. Since 2010, the WeNMR project (www.wenmr.eu) has implemented numerous web-based services to facilitate the use of advanced computational tools by researchers in the field, using the high throughput computing infrastructure provided by EGI. These services have been further developed in subsequent initiatives under H2020 projects and are now operating as Thematic Services in the European Open Science Cloud portal (www.eosc-portal.eu), sending >12 millions of jobs and using around 4,000 CPU-years per year. Here we review 10 years of successful e-infrastructure solutions serving a large worldwide community of over 23,000 users to date, providing them with user-friendly, web-based solutions that run complex workflows in structural biology. The current set of active WeNMR portals are described, together with the complex backend machinery that allows distributed computing resources to be harvested efficiently.

scholarly journals SUBSTRA: Supervised Bayesian Patient Stratification

2019 ◽  
Vol 35 (18) ◽  
pp. 3263-3272
Author(s):  
Sahand Khakabimamaghani ◽  
Yogeshwar D Kelkar ◽  
Bruno M Grande ◽  
Ryan D Morin ◽  
Martin Ester ◽  
...  
Keyword(s):  
Drug Response ◽  
Bayesian Method ◽  
State Of The Art ◽  
Transplant Rejection ◽  
Simulated Data ◽  
Predictive Performance ◽  
Response Prediction ◽  
Supplementary Information ◽  
Patient Stratification ◽  
Feature Importance

Abstract Motivation Patient stratification methods are key to the vision of precision medicine. Here, we consider transcriptional data to segment the patient population into subsets relevant to a given phenotype. Whereas most existing patient stratification methods focus either on predictive performance or interpretable features, we developed a method striking a balance between these two important goals. Results We introduce a Bayesian method called SUBSTRA that uses regularized biclustering to identify patient subtypes and interpretable subtype-specific transcript clusters. The method iteratively re-weights feature importance to optimize phenotype prediction performance by producing more phenotype-relevant patient subtypes. We investigate the performance of SUBSTRA in finding relevant features using simulated data and successfully benchmark it against state-of-the-art unsupervised stratification methods and supervised alternatives. Moreover, SUBSTRA achieves predictive performance competitive with the supervised benchmark methods and provides interpretable transcriptional features in diverse biological settings, such as drug response prediction, cancer diagnosis, or kidney transplant rejection. Availability and implementation The R code of SUBSTRA is available at https://github.com/sahandk/SUBSTRA. Supplementary information Supplementary data are available at Bioinformatics online.

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