scholarly journals Frontiers and opportunities in bioenergy crop microbiome research networks

2021 ◽  
Author(s):  
Adina Howe ◽  
Gregory Bonito ◽  
Ming-Yi Chou ◽  
Melissa Cregger ◽  
Anna Fedders ◽  
...  
Keyword(s):  
Best Practices ◽  
Department Of Energy ◽  
Plant Metabolites ◽  
Related Data ◽  
Hands On ◽  
Microbiome Research ◽  
Microbe Interactions ◽  
Meta Analyses ◽  
Microbiome Data ◽  
Wide Scientific Community

Researchers from across the four U.S. Department of Energy Bioenergy Research Centers engaged in a microbiome workshop that focused on identifying challenges and collaboration opportunities to better understand bioenergy-relevant plant–microbe interactions. The virtual workshop included hands-on educational sessions and a keynote address on current best practices in microbiome science and community microbiome standards, as well as breakout sessions aimed at identifying microbiome-related data and measurements that should be prioritized, opportunities for and barriers to integrating plant metabolites to microbiome research, and strategies for more effectively integrating microbiome data and processes into existing models. Based on participant discussion, key findings of the workshop were the need to prioritize scaling data sharing across BRCs and the broader research community and securing collaborative infrastructure in the areas of microbiome-ecosystem modeling and molecular plant-microbe interactions. This workshop review highlights additional main findings from this event, to encourage cross-site and more holistic meta-analyses while promoting wide scientific community engagement across plant microbiome sciences.

scholarly journals Benchmarking microbiome transformations favors experimental quantitative approaches to address compositionality and sampling depth biases

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Verónica Lloréns-Rico ◽  
Sara Vieira-Silva ◽  
Pedro J. Gonçalves ◽  
Gwen Falony ◽  
Jeroen Raes
Keyword(s):  
Microbial Communities ◽  
Quantitative Methods ◽  
Microbial Load ◽  
Metagenomic Sequencing ◽  
Sampling Depth ◽  
Microbiome Research ◽  
Microbiome Data ◽  
The Impact ◽  
Analytical Approaches ◽  
Quantitative Approaches

AbstractWhile metagenomic sequencing has become the tool of preference to study host-associated microbial communities, downstream analyses and clinical interpretation of microbiome data remains challenging due to the sparsity and compositionality of sequence matrices. Here, we evaluate both computational and experimental approaches proposed to mitigate the impact of these outstanding issues. Generating fecal metagenomes drawn from simulated microbial communities, we benchmark the performance of thirteen commonly used analytical approaches in terms of diversity estimation, identification of taxon-taxon associations, and assessment of taxon-metadata correlations under the challenge of varying microbial ecosystem loads. We find quantitative approaches including experimental procedures to incorporate microbial load variation in downstream analyses to perform significantly better than computational strategies designed to mitigate data compositionality and sparsity, not only improving the identification of true positive associations, but also reducing false positive detection. When analyzing simulated scenarios of low microbial load dysbiosis as observed in inflammatory pathologies, quantitative methods correcting for sampling depth show higher precision compared to uncorrected scaling. Overall, our findings advocate for a wider adoption of experimental quantitative approaches in microbiome research, yet also suggest preferred transformations for specific cases where determination of microbial load of samples is not feasible.

scholarly journals Best practices for MRI systematic reviews and meta‐analyses

2018 ◽  
Vol 49 (7) ◽  
pp. e51-e64 ◽  
Author(s):  
Trevor A. McGrath ◽  
Patrick M. Bossuyt ◽  
Paul Cronin ◽  
Jean‐Paul Salameh ◽  
Noémie Kraaijpoel ◽  
...  
Keyword(s):  
Best Practices ◽  
Systematic Reviews ◽  
Meta Analyses

A Framework for Engineering Dissection Exercise Creation and Implementation

2009 ◽  
Author(s):  
Kathleen M. Hart ◽  
Steven B. Shooter ◽  
Charles J. Kim
Keyword(s):  
Active Learning ◽  
Best Practices ◽  
Reverse Engineering ◽  
Engineering Education ◽  
Learning Outcomes ◽  
Positive Impact ◽  
Rigorous Approach ◽  
Engineering Activity ◽  
Hands On ◽  
Different Levels

Hands-on product dissection and reverse engineering exercises have been shown to have a positive impact on engineering education, and many universities have incorporated such exercises in their curriculum. The CIBER-U project seeks to examine the potential to utilize cyberinfrastructure to enhance these active-learning exercises. We have formulated a framework for product dissection and reverse engineering activity creation to support a more rigorous approach to assessing other exercises for satisfaction of the CIBER-U project goals and adapting the best practices. This framework is driven by the fulfillment of learning outcomes and considers the maturity of students at different levels. Prototype exercises developed with the framework are presented. The approach is sufficiently general that it can be applied to the consideration and adaption of other types of exercises while ensuring satisfaction of the established goals.

scholarly journals Streaming histogram sketching for rapid microbiome analytics

2018 ◽  
Author(s):  
Will P. M. Rowe ◽  
Anna Paola Carrieri ◽  
Cristina Alcon-Giner ◽  
Shabhonam Caim ◽  
Alex Shaw ◽  
...  
Keyword(s):  
Locality Sensitive Hashing ◽  
Genomic Research ◽  
Compact Representation ◽  
Sample Type ◽  
Sequencing Data ◽  
Similarity Estimation ◽  
Microbiome Research ◽  
Microbiome Data ◽  
Similarity Searches

AbstractMotivationThe growth in publically available microbiome data in recent years has yielded an invaluable resource for genomic research; allowing for the design of new studies, augmentation of novel datasets and reanalysis of published works. This vast amount of microbiome data, as well as the widespread proliferation of microbiome research and the looming era of clinical metagenomics, means there is an urgent need to develop analytics that can process huge amounts of data in a short amount of time.To address this need, we propose a new method for the compact representation of microbiome sequencing data using similarity-preserving sketches of streaming k-mer spectra. These sketches allow for dissimilarity estimation, rapid microbiome catalogue searching, and classification of microbiome samples in near real-time.ResultsWe apply streaming histogram sketching to microbiome samples as a form of dimensionality reduction, creating a compressed ‘histosketch’ that can be used to efficiently represent microbiome k-mer spectra. Using public microbiome datasets, we show that histosketches can be clustered by sample type using pairwise Jaccard similarity estimation, consequently allowing for rapid microbiome similarity searches via a locality sensitive hashing indexing scheme. Furthermore, we show that histosketches can be used to train machine learning classifiers to accurately label microbiome samples. Specifically, using a collection of 108 novel microbiome samples from a cohort of premature neonates, we trained and tested a Random Forest Classifier that could accurately predict whether the neonate had received antibiotic treatment (95% accuracy, precision 97%) and could subsequently be used to classify microbiome data streams in less than 12 seconds.We provide our implementation, Histosketching Using Little K-mers (HULK), which can histosketch a typical 2GB microbiome in 50 seconds on a standard laptop using 4 cores, with the sketch occupying 3000 bytes of disk space.AvailabilityOur implementation (HULK) is written in Go and is available at: https://github.com/will-rowe/hulk (MIT License)

scholarly journals QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science

2018 ◽  
Author(s):  
Evan Bolyen ◽  
Jai Ram Rideout ◽  
Matthew R Dillon ◽  
Nicholas A Bokulich ◽  
Christian Abnet ◽  
...  
Keyword(s):  
Data Science ◽  
Temporal Analysis ◽  
Data Provenance ◽  
Policy Makers ◽  
Shotgun Metagenomics ◽  
Spatial And Temporal Analysis ◽  
Microbiome Research ◽  
Scientists And Engineers ◽  
Visualization Tools ◽  
Microbiome Data

We present QIIME 2, an open-source microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers. QIIME 2 provides new features that will drive the next generation of microbiome research. These include interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.

Prevalence of Suicidal Ideation in Patients with Covid-19 in the World: Systematic Review and Meta-Analysis Protocol (Preprint)

2021 ◽  
Author(s):  
Alireza Razzaghi ◽  
Fatemeh Sadat Asgarian ◽  
Hossein Akbari
Keyword(s):  
Suicidal Ideation ◽  
Critical Appraisal ◽  
Suicide Ideation ◽  
Meta Analysis ◽  
Prevalence Data ◽  
Related Data ◽  
The World ◽  
Review Study ◽  
Meta Analyses ◽  
Analysis Protocol

BACKGROUND The pandemic of Covid-19 started in China in late 2019 and has spread rapidly around the world. Psychological problems such as suicide ideation of Covid-19 is one of the main consequences of this pandemic, which needs more attention OBJECTIVE This study aims to determine a comprehensive estimate of the prevalence of suicidal ideation in patients with Covid-19 in the world. METHODS The review study will be based on the following databases: databases of Web of Sciences, Mediline/Pubmed, Proquest, Scopus, Science Direct. This study is limited to original studies published in peer-reviewed journals in English. RESULTS The quality assessment of studies will be done using the Joanna Briggs Institute’s (JBI) critical appraisal checklist for reporting the prevalence data. The overall synthetized measurement will be presented as Prevalence with 95% confidence intervals. CONCLUSIONS This review and meta-analyses will be the first study that explores the prevalence of suicide ideation related to Covid-19. Summarizing the related data can create an image of the dimensions of the problem across the world and provide plans to prevent that.

scholarly journals Community-Driven Metadata Standards for Agricultural Microbiome Research

2020 ◽  
Vol 4 (2) ◽  
pp. 115-121 ◽  
Author(s):  
J. P. Dundore-Arias ◽  
E. A. Eloe-Fadrosh ◽  
L. M. Schriml ◽  
G. A. Beattie ◽  
F. P. Brennan ◽  
...  
Keyword(s):  
Crop Management ◽  
Crop Productivity ◽  
Field Sampling ◽  
Minimum Information ◽  
Metadata Standards ◽  
Starting Point ◽  
Microbiome Research ◽  
Widespread Availability ◽  
Microbiome Data ◽  
Data Variation

Accelerating the pace of microbiome science to enhance crop productivity and agroecosystem health will require transdisciplinary studies, comparisons among datasets, and synthetic analyses of research from diverse crop management contexts. However, despite the widespread availability of crop-associated microbiome data, variation in field sampling and laboratory processing methodologies, as well as metadata collection and reporting, significantly constrains the potential for integrative and comparative analyses. Here we discuss the need for agriculture-specific metadata standards for microbiome research, and propose a list of “required” and “desirable” metadata categories and ontologies essential to be included in a future minimum information metadata standards checklist for describing agricultural microbiome studies. We begin by briefly reviewing existing metadata standards relevant to agricultural microbiome research, and describe ongoing efforts to enhance the potential for integration of data across research studies. Our goal is not to delineate a fixed list of metadata requirements. Instead, we hope to advance the field by providing a starting point for discussion, and inspire researchers to adopt standardized procedures for collecting and reporting consistent and well-annotated metadata for agricultural microbiome research.

Can interpretive graphics influence visitor behavior in an exhibit space?

2018 ◽  
Vol 23 (1) ◽  
pp. 47-56
Author(s):  
Allison M. Price ◽  
Jessica C. Monahan ◽  
Rachel Bergren
Keyword(s):  
Best Practices ◽  
Formative Evaluation ◽  
Collaborative Planning ◽  
Evaluation Methods ◽  
Black Rhinoceros ◽  
Visitor Behavior ◽  
Hands On ◽  
Personal Media ◽  
Data Informed ◽  
Lincoln Park

Exhibit signage and graphics projects are most successful when they involve collaborative planning and formative evaluation throughout the process. Lincoln Park Zoo set out to combine interpretive best practices and visitor evaluation methods for the newly renovated eastern black rhinoceros yard in 2010. Evaluation methods included prototyping, visitor tracking, and informal interviews. After installation of the new graphics, visitor time spent looking at both the signs and the exhibit increased. Results were most significant among male visitors. The study indicates that hands-on non-personal media of this nature can have a significant effect on visitor behavior in an exhibit space. It also provides a model for making data-informed decisions regardless of limited budgets or resources.

scholarly journals Toward a Global Public Repository of Community Protocols to Encourage Best Practices in Biomolecular Ocean Observing and Research

2021 ◽  
Vol 8 ◽  
Author(s):  
Robyn M. Samuel ◽  
Raissa Meyer ◽  
Pier Luigi Buttigieg ◽  
Neil Davies ◽  
Nicholas W. Jeffery ◽  
...  
Keyword(s):  
Best Practices ◽  
Value Chain ◽  
Global Ocean ◽  
Research Groups ◽  
Ocean Science ◽  
Microbiome Research ◽  
Publicly Supported ◽  
And Function ◽  
Ocean Observing ◽  
Insight Into

Biomolecular ocean observing and research is a rapidly evolving field that uses omics approaches to describe biodiversity at its foundational level, giving insight into the structure and function of marine ecosystems over time and space. It is an especially effective approach for investigating the marine microbiome. To mature marine microbiome research and operations within a global ocean biomolecular observing network (OBON) for the UN Decade of Ocean Science for Sustainable Development and beyond, research groups will need a system to effectively share, discover, and compare “omic” practices and protocols. While numerous informatic tools and standards exist, there is currently no global, publicly-supported platform specifically designed for sharing marine omics [or any omics] protocols across the entire value-chain from initiating a study to the publication and use of its results. Toward that goal, we propose the development of the Minimum Information for an Omic Protocol (MIOP), a community-developed guide of curated, standardized metadata tags and categories that will orient protocols in the value-chain for the facilitated, structured, and user-driven discovery of suitable protocol suites on the Ocean Best Practices System. Users can annotate their protocols with these tags, or use them as search criteria to find appropriate protocols. Implementing such a curated repository is an essential step toward establishing best practices. Sharing protocols and encouraging comparisons through this repository will be the first steps toward designing a decision tree to guide users to community endorsed best practices.

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