dkNET Webinar: dkNET Hypothesis Center Live Demo 09/24/2021
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Abstract dkNET is creating a hub for big data and hypothesis generation, bringing together a collection of online tools that will allow researchers to explore different datasets and utilize analytics and visualization tools. The dkNET Hypothesis Center phenotype-genotype analytics module is currently performed utilizing data from the Signaling Pathways Project (SPP), and the Mouse Metabolic Phenotyping Centers (MMPC). Upcoming resources include the Human Islet Research Network Resource Browser, Appyters, Type 1 Diabetes Knowledge Portal,...and more. Through detailed tutorials and integrating different resources, the power of the dkNET Hypothesis Center can help answer the questions of immediate relevance to your research. What you will learn: - Introduction of the dkNET Hypothesis Center - How to navigate and access tutorials that will teach you how to use FAIR data and bioinformatics tool(s) - How the dkNET Hypothesis Center can assist in answering your research questions and generating hypotheses Presenter: Jeffrey Grethe, PhD, dkNET Principal Investigator, University of California San Diego Upcoming webinars schedule: https://dknet.org/about/webinar
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Tendances (20)
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Presenter: Jeffrey Grethe, PhD, dkNET Principal Investigator, University of California San Diego
Abstract
The dkNET (NIDDK Information Network) team is announcing an exciting new service - Biomed Resource Watch (BRW, https://scicrunch.org/ResourceWatch), a knowledge base for aggregating and disseminating known problems and performance information about research resources such as antibodies, cell lines, and tools. We aggregate trustworthy information from authorized sources such as Cellosaurus, Antibody Registry, Human Protein Atlas, ENCODE, and many more. In addition, BRW includes antibody specificity text mining information extracted from the literature via natural language processing. BRW provides researchers and curators an easy-to-use interface to report their claims about a specific resource. Researchers can check information about a resource before planning their experiments via BRW-enhanced Resource Reports. This new service aims to help improve efficiency in selecting appropriate resources, enhancing scientific rigor and reproducibility, and promoting a FAIR (Findable, Accessible, Interoperable, Reusable) research resource ecosystem in the biomedical research community.
Join us for a webinar to introduce the following resources & topics:
1. An overview of dkNET
2. How Resource Reports benefit you
3. Biomed Resource Watch
3.1 Navigating Biomed Resource Watch
3.2 How to Submit a Claim
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Office Hours: NIH Data Management and Sharing Mandate 05/03/2024
Presenter: Jeffrey Grethe, PhD, Principal Investigator of NIDDK Information Network (dkNET), Center for Research in Biological Systems, University of California San Diego
For all proposals submitted on/after January 25 2023, NIH requires the sharing of data from all NIH funded studies. Do you have appropriate data management practices and sharing plans in place to meet these requirements? Have questions or need some help? Join the dkNET office hours to learn about NIH’s policy (NOT-OD-21-013) and resources that could help.
*Previous Office Hours Slides and Recording: https://dknet.org/rin/research-data-management
Upcoming Webinars Schedule: https://dknet.org/about/webinar
dkNET Webinar: Discovering and Evaluating Antibodies, Cell Lines, Software To...
Abstract
dkNET’s Resource Reports (https://dknet.org/rin/rrids) enable researchers to discover research resources that would be useful for their research. The resource report integrated data set and analytics platform combines Research Resource Identifiers (RRIDs), text mining and data aggregation to help you identify key biomedical resources, track these resources, and compare their performance. Resource Reports offer a detailed overview of each resource along with citation metrics from the biomedical literature and even information about what resources have been used together. You'll gain insights about who is using particular resources and how the community views those resources, including usage in published protocols.
The dkNET Co-PI, Dr Jeffrey Grethe, will give you live demos during this webinar, including:
- How to find and select a research resource such as an antibody or a cell line
- How to find Research Resource Identifiers (RRIDs) and proper citation of your resources
- How to register resources to obtain RRIDs if the resources do not exist in the system
We hope this short webinar will provide an opportunity to use this tool to shape your research activities.
Presenter: Jeffrey Grethe, PhD, dkNET Co-Principal Investigator, University of California San Diego
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Annual Meeting - June 2017
The dkNET annual meeting provided progress reports on recommendations from 2016. New resources were added to the registry including datasets, centers, and repositories. The dkNET site was improved with updated interfaces for browsing resources and new visualization tools. Efforts to support rigor and reproducibility included expanding RRID adoption and developing API services to integrate dkNET data. Plans are underway to provide more robust tracking of research resources.
The NIH Commons: A Cloud-based Training Environment
Presented at ISMB 2016 in Orlando, Florida, July 11, 2016. As the Commons emerges as a platform scientists need to be trained in its use.
RDMkit, a Research Data Management Toolkit. Built by the Community for the ...
https://datascience.nih.gov/news/march-data-sharing-and-reuse-seminar 11 March 2022
Starting in 2023, the US National Institutes of Health (NIH) will require institutes and researchers receiving funding to include a Data Management Plan (DMP) in their grant applications, including the making their data publicly available. Similar mandates are already in place in Europe, for example a DMP is mandatory in Horizon Europe projects involving data.
Policy is one thing - practice is quite another. How do we provide the necessary information, guidance and advice for our bioscientists, researchers, data stewards and project managers? There are numerous repositories and standards. Which is best? What are the challenges at each step of the data lifecycle? How should different types of data? What tools are available? Research Data Management advice is often too general to be useful and specific information is fragmented and hard to find.
ELIXIR, the pan-national European Research Infrastructure for Life Science data, aims to enable research projects to operate “FAIR data first”. ELIXIR supports researchers across their whole RDM lifecycle, navigating the complexity of a data ecosystem that bridges from local cyberinfrastructures to pan-national archives and across bio-domains.
The ELIXIR RDMkit (https://rdmkit.elixir-europe.org (link is external)) is a toolkit built by the biosciences community, for the biosciences community to provide the RDM information they need. It is a framework for advice and best practice for RDM and acts as a hub of RDM information, with links to tool registries, training materials, standards, and databases, and to services that offer deeper knowledge for DMP planning and FAIR-ification practices.
Launched in March 2021, over 120 contributors have provided nearly 100 pages of content and links to more than 300 tools. Content covers the data lifecycle and specialized domains in biology, national considerations and examples of “tool assemblies” developed to support RDM. It has been accessed by over 123 countries, and the top of the access list is … the United States.
The RDMkit is already a recommended resource of the European Commission. The platform, editorial, and contributor methods helped build a specialized sister toolkit for infectious diseases as part of the recently launched BY-COVID project. The toolkit’s platform is the simplest we could manage - built on plain GitHub - and the whole development and contribution approach tailored to be as lightweight and sustainable as possible.
In this talk, Carole and Frederik will present the RDMkit; aims and context, content, community management, how folks can contribute, and our future plans and potential prospects for trans-Atlantic cooperation.
Data policy must be partnered with data practice. Our researchers need to be the best informed in order to meet these new data management and data sharing mandates.
BD2K Update
This document summarizes an update on the Big Data to Knowledge (BD2K) initiative at the National Institutes of Health (NIH). It discusses progress made in the first year of BD2K funding in three key areas: advancing data science research through centers and targeted awards; sharing data and software through the development of indexing tools and standards; and expanding training programs. It outlines funding amounts and recipient numbers for fiscal year 2015. Future plans are outlined through 2021 with the goals of further developing tools and applications, expanding the data sharing commons, and increasing training and sustainability efforts.
D4Science Data infrastructure: a facilitator for a FAIR data management
D4Science is a hybrid data infrastructure that integrates technologies to provide elastic access and usage of data and data management capabilities. It hosts over 50 virtual research environments for over 2500 scientists across 44 countries. D4Science aims to facilitate FAIR (Findable, Accessible, Interoperable, Re-usable) data management by assigning unique identifiers and rich metadata to resources, publishing catalogs to enable discovery, making resources available through standards, adding metadata in multiple formats, and requiring licenses and provenance to promote reuse.
D4Science Data Infrastructure - Facilitator for a FAIR Data Management
Presented by Pasquale Pagano of CNR-ISTI at the FAIR Data Management event, 14-15 November in Florence, Italy
dkNET Webinar: Creating and Sustaining a FAIR Biomedical Data Ecosystem 10/09...
Abstract
In this presentation, Susan Gregurick, Ph.D., Associate Director of Data Science and Director, Office of Data Science Strategy at the National Institutes of Health, will share the NIH’s vision for a modernized, integrated FAIR biomedical data ecosystem and the strategic roadmap that NIH is following to achieve this vision. Dr. Gregurick will highlight projects being implemented by team members across the NIH’s 27 institutes and centers and will ways that industry, academia, and other communities can help NIH enable a FAIR data ecosystem. Finally, she will weave in how this strategy is being leveraged to address the COVID-19 pandemic.
Presenter: Susan Gregurick, Ph.D., Associate Director of Data Science and Director, Office of Data Science Strategy at the National Institutes of Health
dkNET Webinar Information: https://dknet.org/about/webinar
Enabling better science: Results and vision of the OpenAIRE infrastructure an...
Presentation by Paolo Manghi (CNR - OpenAIRE technical manager) at the 6th RDA Plenary, Paris, September 2015.
Enabling better science - Results and vision of the OpenAIRE infrastructure a...
The document discusses enabling better science through open access to research outputs. It describes the OpenAIRE infrastructure and the Research Data Alliance (RDA) Data Publishing Working Group. OpenAIRE provides services to link publications, research data, projects and initiatives. The RDA group aims to create an open service for linking datasets to publications. OpenAIRE and PANGAEA are developing a beta data-literature linking service to increase discovery and reuse of research outputs.
Mendeley Data: Enhancing Data Discovery, Sharing and Reuse
Slides for the NIH Workshop, 2/11/20 'The Role of Generalist and Institutional Repositories to Enhance Data Discoverability and Reuse
Hahn "Wikidata as a hub to library linked data re-use"
Hahn "Wikidata as a hub to library linked data re-use"National Information Standards Organization (NISO)
This presentation was provided by Jim Hahn of The University of Pennsylvania, during the NISO event "Transforming Search: What the Information Community Can and Should Build." The virtual conference was held on August 26, 2020.EMBL Australian Bioinformatics Resource AHM - Data Commons
This document discusses the development of the NIH Data Commons, which aims to create a shared framework and infrastructure for biomedical data. It notes the increasing amounts of data being generated and the need for data sharing and interoperability. The Data Commons framework treats data, tools, and publications as digital objects that are findable, accessible, interoperable and reusable. Current pilots include deploying reference datasets in the cloud, indexing data and tools, and a credits system for cloud resources. Challenges discussed include metrics, costs, standards, incentives and sustainability. The framework's relevance for supporting open data in Australia is also addressed.
STI 2022 - Generating large-scale network analyses of scientific landscapes i...
The growth of large, programatically accessible bibliometrics databases presents new opportunities for complex analyses of publication metadata. In addition to providing a wealth of information about authors and institutions, databases such as those provided by Dimensions also provide conceptual information and links to entities such as grants, funders and patents. However, data is not the only challenge in evaluating patterns in scholarly work: These large datasets can be challenging to integrate, particularly for those unfamiliar with the complex schemas necessary for accommodating such heterogeneous information, and those most comfortable with data mining may not be as experienced in data visualisation. Here, we present an open-source Python library that streamlines the process accessing and diagramming subsets of the Dimensions on Google BigQuery database and demonstrate its use on the freely available Dimensions COVID-19 dataset. We are optimistic that this tool will expand access to this valuable information by streamlining what would otherwise be multiple complex technical tasks, enabling more researchers to examine patterns in research focus and collaboration over time.
OpenAIRE services and tools - 6th National Open Access Conference and OpenAIR...
OpenAIRE provides services and tools to support open science, including:
1. An e-infrastructure that connects publications repositories, research data repositories, CRIS systems, registries, open access journals, and software repositories.
2. Services for content providers, funders, and researchers, including validation, enrichment, and discovery of publications, data, projects, and software.
3. APIs, search interfaces, and tools to link research outputs like publications and data to projects and funders.
OpenAIRE services and tools - 6th National Open Access Conference and OpenAIR...
OpenAIRE provides services and tools to support open science, including:
1. An e-infrastructure that connects publications repositories, research data repositories, CRIS systems, registries, open access journals, and software repositories.
2. Services for content providers, funders, and researchers, including validation, enrichment, and discovery of publications, data, projects, and software.
3. APIs, search interfaces, and tools to link research outputs to projects and funders and support reporting and analysis of open access trends and research impact.
Paul hu bupdate_i_digbio_ecn_2012
This document summarizes an update from the Entomological Collections Network meeting in 2012. It discusses the iDigBio initiative to facilitate the digitization of biodiversity collections data through developing standards, providing portal access to data, and planning for long-term sustainability. It describes the seven Thematic Collection Networks and over 130 participating institutions. It provides details on the development of the iDigBio HUB portal and API to enable access to digitized specimen records along with upcoming workshops and activities.
Similaire à dkNET Webinar: dkNET Hypothesis Center Live Demo 09/24/2021 (20)
dkNET Office Hours - "Are You Ready for 2023: New NIH Data Management and Sha...
dkNET Office Hours - "Are You Ready for 2023: New NIH Data Management and Sha...
dkNET Webinar: Discover the Latest from dkNET - Biomed Resource Watch 06/02/2023
dkNET Webinar: Discover the Latest from dkNET - Biomed Resource Watch 06/02/2023
dkNET Office Hours: NIH Data Management and Sharing Mandate 05/03/2024
dkNET Office Hours: NIH Data Management and Sharing Mandate 05/03/2024
dkNET Webinar: Discovering and Evaluating Antibodies, Cell Lines, Software To...
dkNET Webinar: Discovering and Evaluating Antibodies, Cell Lines, Software To...
The NIH Commons: A Cloud-based Training Environment
The NIH Commons: A Cloud-based Training Environment
RDMkit, a Research Data Management Toolkit. Built by the Community for the ...
RDMkit, a Research Data Management Toolkit. Built by the Community for the ...
D4Science Data infrastructure: a facilitator for a FAIR data management
D4Science Data infrastructure: a facilitator for a FAIR data management
D4Science Data Infrastructure - Facilitator for a FAIR Data Management
D4Science Data Infrastructure - Facilitator for a FAIR Data Management
dkNET Webinar: Creating and Sustaining a FAIR Biomedical Data Ecosystem 10/09...
dkNET Webinar: Creating and Sustaining a FAIR Biomedical Data Ecosystem 10/09...
Enabling better science: Results and vision of the OpenAIRE infrastructure an...
Enabling better science: Results and vision of the OpenAIRE infrastructure an...
Enabling better science - Results and vision of the OpenAIRE infrastructure a...
Enabling better science - Results and vision of the OpenAIRE infrastructure a...
Mendeley Data: Enhancing Data Discovery, Sharing and Reuse
Mendeley Data: Enhancing Data Discovery, Sharing and Reuse
Hahn "Wikidata as a hub to library linked data re-use"
Hahn "Wikidata as a hub to library linked data re-use"
EMBL Australian Bioinformatics Resource AHM - Data Commons
EMBL Australian Bioinformatics Resource AHM - Data Commons
STI 2022 - Generating large-scale network analyses of scientific landscapes i...
STI 2022 - Generating large-scale network analyses of scientific landscapes i...
OpenAIRE services and tools - 6th National Open Access Conference and OpenAIR...
OpenAIRE services and tools - 6th National Open Access Conference and OpenAIR...
OpenAIRE services and tools - 6th National Open Access Conference and OpenAIR...
OpenAIRE services and tools - 6th National Open Access Conference and OpenAIR...
Plus de dkNET
dkNET Webinar: The 4DN Data Portal - Data, Resources and Tools to Help Elucid...
Presenter: Andrew Schroeder, PhD. Project Manager & Senior Data Curator, 4D Nucleome Data Coordination and Integration Center (4DN-DCIC), Park Lab, Department of Biomedical Informatics, Harvard Medical School
Abstract
The Common Fund 4D Nucleome program, currently in its 9th year, is a consortium of researchers that aims to understand the principles behind the three-dimensional organization of the nucleus and how this organization can change over time to affect a variety of cellular processes. The 4DN Data Portal (data.4dnucleome.org) is an expanding resource hosting data generated by the 4DN Network and other reference nucleomics data sets. The portal provides tools for search, exploration, visualization, and download. An overview of the data portal, highlighting available data, how it can be found, visualized and used for analyses will be presented.
The top 3 key questions that the 4DN data portal can answer:
1. Are there significant sites of long-range chromatin contacts near my gene or region of interest?
2. What omics datasets are available for my tissue of interest?
3. Are there imaging datasets available that are relevant to my tissue of interest?
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar "Texera: A Scalable Cloud Computing Platform for Sharing Data a...
Presenter: Chen Li, PhD. Professor, Department of Computer Science, University of California Irvine
Abstract
Many data analytics projects have collaborators with complementary backgrounds, including biologists, bioinformaticians, computer scientists, and AI/ML experts. Many of them have limited experience to code, set up a computing infrastructure, and use MLmodels. Existing tools and services, such as email attachments, GitHub, and Google Drive are inefficient for sharing data and analyses. In this talk, we present an open source system called Texera that provides a cloud computing platform for collaborators to share data and analyses as workflows. After seven years of development, the system has a rich set of powerful features, such as shared editing, shared execution, version control, commenting, debugging, user-defined functions in multiple languages (e.g., Python, R, Java), and support of state-of-the-art AI/ML techniques. Its backend parallel engine enables scalable computation on large data sets using computing clusters. We will show a demo of the system, and present our vision supported by a recent NIH award, dkNET(NIDDK Information Network, https://dknet.org), to serve the diabetes, endocrinology, and metabolic diseases research communities through the FAIR sharing of data and knowledge.
Resource link: https://github.com/Texera/texera
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar: Unlocking the Power of FAIR Data Sharing with ImmPort 04/12/2024
Presenter: Sanchita Bhattacharya, ImmPort Science Program Lead, Bakar Computational Health Sciences Institute UCSF
Abstract
The Immunology Database and Analysis Portal (ImmPort, https://www.immport.org/home) is a domain-specific data repository for immunology-related data which is funded by the National Institutes of Health, National Institute of Allergy and Infectious Diseases, and Division of Allergy, Immunology, and Transplantation. ImmPort has been making scientific data Findable, Accessible, Interoperable, and Reusable (FAIR) for over 20 years. ImmPort data sets encompass over 7 million experimental results across 160 diseases and conditions, including data related to diabetes, kidney and liver transplantation, celiac disease, and many more conditions. In this webinar, participants will learn about data management and sharing through ImmPort, as well as finding and leveraging data sets of interest for research.
The top 3 key questions that the ImmPort can answer:
1. How can researchers share data through ImmPort to comply with the NIH Data Management and Sharing policy?
2. How does ImmPort support FAIR data and why is this powerful for research?
3. What scientific data does ImmPort house that would be of interest to NIDDK researchers?
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar: Tabula Sapiens 03/22/2024
Presenter: Angela Oliveira Pisco , PhD
Abstract
Although the genome is often called the blueprint of an organism, it is perhaps more accurate to describe it as a parts list composed of the various genes that may or may not be used in the different cell types of a multicellular organism. While nearly every cell in the body has essentially the same genome, each cell type makes different use of that genome and expresses a subset of all possible genes. This has motivated efforts to characterize the molecular composition of various cell types within humans and multiple model organisms, both by transcriptional and proteomic approaches. We created a human reference atlas comprising nearly 500,000 cells from 24 different tissues and organs, many from the same donor. This atlas enabled molecular characterization of more than 400 cell types, their distribution across tissues, and tissue-specific variation in gene expression. One caveat to current approaches to make cell atlases is that individual organs are often collected at different locations, collected from different donors, and processed using different protocols. Controlled comparisons of cell types between different tissues and organs are especially difficult when donors differ in genetic background, age, environmental exposure, and epigenetic effects. To address this, we developed an approach to analyzing large numbers of organs from the same individual. We collected multiple tissues from individual human donors and performed coordinated single-cell transcriptome analyses on live cells. The donors come from a range of ethnicities, are balanced by gender, have a mean age of 51 years, and have a variety of medical backgrounds. Tissue experts used a defined cell ontology terminology to annotate cell types consistently across the different tissues, leading to a total of 475 distinct cell types with reference transcriptome profiles. The Tabula Sapiens also provided an opportunity to densely and directly sample the human microbiome throughout the gastrointestinal tract. The Tabula Sapiens has revealed discoveries relating to shared behavior and subtle, organ-specific differences across cell types. We found T cell clones shared between organs and characterized organ-dependent hypermutation rates among B cells. Endothelial cells and macrophages are shared across tissues, often showing subtle but clear differences in gene expression. We found an unexpectedly large and diverse amount of cell type–specific RNA splice variant usage and discovered and validated many previously undefined splices. The intestinal microbiome was revealed to have nonuniform species distributions down to the 3-inch (7.62-cm) length scale. These are but a few examples of how the Tabula Sapiens represents a broadly useful reference...Full abstract: https://dknet.org/about/blog/2726
Resource link: https://tabula-sapiens-portal.ds.czbiohub.org
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar "The Multi-Omic Response to Exercise Training Across Rat Tissue...
Presenter: Malene Lindholm, PhD, Instructor, Department of Medicine, Stanford University
Abstract
The Molecular Transducers of Physical Activity Consortium (MoTrPAC) aims to map the molecular responses to exercise and training to elucidate how exercise improves health and prevents disease. The first MoTrPAC data provides an extensive temporal map of the dynamic multi-omic response to endurance training across multiple rat tissues. All results can be viewed, interrogated, and downloaded in a user-friendly, publicly accessible data portal (https://motrpac-data.org). The MoTrPAC data compendium includes transcriptomics, proteomics, metabolomics, phosphoproteomics, acetylproteomics, ubiquitylproteomics, DNA methylation, chromatin accessibility, and multiplexed immunoassay data. This compilation constitutes of 211 datasets across 19 tissues, 25 molecular assays, and 4 training time points in adult male and female rats. Over 35,000 analytes were found to be differentially regulated in response to endurance training, with many displaying sexual dimorphism. We observed a male-specific recruitment of immune cells to adipose tissues and an anticorrelated transcriptional response in the adrenal gland related to the stress response. Temporal multi-omic and multi-tissue integration demonstrated similar temporal responses in the heart and skeletal muscle, reflecting a concerted adaptation of mitochondrial biogenesis and metabolism. Integrative multi-omic network analysis revealed connections between the heat shock-mediated stress response and mitochondrial biogenesis. Training increased phospholipids and decreased triacylglycerols in the liver, and there were extensive changes to mitochondrial protein acetylation. Many changes were relevant for human health conditions, such as non-alcoholic fatty liver disease, inflammatory bowel disease, cardiovascular wellness, and tissue damage and repair. Altogether, this MoTrPAC resource provides an unprecedented view of the effects of exercise across an organism, revealing mechanistic details of how exercise impacts mammalian health. The MoTrPAC data hub is the primary online resource to disseminate this large-scale multi-omics data.
The top 3 questions that the MoTrPAC resource can answer:
1. What is the multi-omic response to endurance exercise across different tissues?
2. What are the top signaling pathways affected in response to exercise and do they differ between males and females?
3. How can the MoTrPAC data hub be utilized to interrogate all the MoTrPAC findings?
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar: The Collaborative Microbial Metabolite Center – Democratizing ...
Presenter: Pieter Dorrestein, PhD, Professor, Skaggs School of Pharmacy and Pharmaceutical Sciences, Department of Pharmacology and Pediatrics, University of California San Diego
Abstract
In the analysis of organs, volatilome, or biofluids, the microbiome influences 15-70% of detectable mass spectrometry molecules. Typically, only 10% of human untargeted metabolomics data can be assigned a molecular structure, with merely 1-2% traceable to microbial origins. Human microbiomes contribute metabolites through the microbial metabolism of host-derived substances, digestion of food and beverage molecules, and de novo assembly using proteins encoded by genetic elements. Despite the significance of microbiome-derived metabolites to human health, there is no centralized knowledge base for community access. To address this, the "Collaborative Microbial Metabolite Center" (CMMC) leverages expertise in mass spectrometry, microbiome innovation, and the GNPS ecosystem to built a knowledgebase. It aims to create a user-accessible microbiome resource, enrich bioactivity knowledge, and facilitate data deposition. The CMMC includes the construction of a knowledge base, MicrobeMASST tool, and health phenotype enrichment workflows, the construction and use will be discussed in this presentation. The use of this ecosystem will be exemplified by the discovery of 20,000 bile acids, many of which were shown to be of microbial origin and linked to diet and IBD.
The top 3 key questions that this resource can answer:
1. How can we leverage the 1000’s of public metabolomics studies to discover microbial metabolites and their organ distributions as well as their phenotypic, including health, associations?
2. If one has an unknown molecule, how can one assess what microbes make a molecule without known structure?
3. How can one contribute to the expansion of the knowledgebase on microbial metabolites?
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar: An Encyclopedia of the Adipose Tissue Secretome to Identify Me...
Presenter: Paul Cohen, MD, PhD, Albert Resnick, M.D. Associate Professor, Rockefeller University
Abstract
White and brown adipocytes not only play a central role in energy storage and combustion but are also dynamic secretory cells that secrete signaling molecules linking levels of energy stores to vital physiological systems. Disruption of the signaling properties of adipocytes, as occurs in obesity, contributes to insulin resistance, type 2 diabetes, and other metabolic disorders. Fat cells have been estimated to secrete over 1,000 polypeptides and microproteins and an even larger number of small molecule metabolites. The great majority of the adipocyte secretome has not been defined or characterized. A major obstacle has been the lack of suitable technologies to quantitatively identify circulating proteins and metabolites, determine their cellular origin, and elucidate their function. Building on key innovations in chemical biology and mass spectrometry, our team is generating an encyclopedia of the white and brown adipocyte secretome in mouse models and humans. Our work has the potential to identify new secreted mediators with roles in obesity, type 2 diabetes, and metabolic diseases, provide a crucial resource for researchers and clinicians, and lead to new biomarkers and therapies.
The top 3 key questions that this resource can answer:
1. What techniques can be used to characterize the secretome of a cell type in vitro and in vivo?
2. What is the full complement of proteins and metabolites secreted by different kinds of adipocytes?
3. How should one prioritize uncharacterized secreted mediators for functional study?
Resource link: https://secrepedia.org/
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar: A Single Cell Atlas of Human and Mouse White Adipose Tissue 11...
Presenter: Margo Emont, PhD. Instructor, Beth Israel Deaconess Medical Center/Harvard Medical School
Abstract
White adipose tissue, once regarded as morphologically and functionally bland, is now recognized to be dynamic, plastic and heterogenous, and is involved in a wide array of biological processes including energy homeostasis, glucose and lipid handling, blood pressure control and host defense. High-fat feeding and other metabolic stressors cause marked changes in adipose morphology, physiology and cellular composition, and alterations in adiposity are associated with insulin resistance, dyslipidemia and type 2 diabetes. Here we provide detailed cellular atlases of human and mouse subcutaneous and visceral white fat at single-cell resolution across a range of body weight. We identify subpopulations of adipocytes, adipose stem and progenitor cells, vascular and immune cells and demonstrate commonalities and differences across species and dietary conditions. We link specific cell types to increased risk of metabolic disease and provide an initial blueprint for a comprehensive set of interactions between individual cell types in the adipose niche in leanness and obesity. These data comprise an extensive resource for the exploration of genes, traits and cell types in the function of white adipose tissue across species, depots and nutritional conditions.
The top 3 key questions that this resource can answer:
1. How specific is my gene of interest to a particular cell type in adipose tissue?
2. Is the gene/pathway that I am studying in mouse adipose tissue also present in human adipose tissue (and is it regulated similarly in low vs high body weight)?
3. What are the changes in gene expression in a specific cell type at low vs high body weight?
Resource link:
https://singlecell.broadinstitute.org/single_cell/study/SCP1376/a-single-cell-atlas-of-human-and-mouse-white-adipose-tissue#study-summary
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar "The National Sleep Research Resource (NSRR) - Opportunities fo...
Presenter: Susan Redline, MD, MPH, Peter C. Farrell Professor of Sleep Medicine, Professor of Epidemiology, Harvard T.H. Chan School of Public Health
Abstract
Experimental, clinical and epidemiological studies have identified multiple inter-relationships of sleep with glucose regulation and metabolic disease. In one meta-analysis, after overweight and family history of diabetes, the next 7 top risk factors for incident diabetes were measures of sleep health. These included poor sleep quality, insomnia, short or extremely long sleep duration, and sleep apnea; each sleep problem was associated with incident diabetes with relative risks ranging from 1.38 to 1.74. A mechanism linking sleep apnea with diabetes is through the effects of intermittent hypoxemia on insulin sensitivity. However, studies using neurophysiological markers of sleep in healthy adults showed that selective reduction of slow wave sleep reduced glucose tolerance by 23%, thus additionally suggesting the importance neurophysiological mechanisms during sleep in glucose regulation. In support of this, longitudinal epidemiological studies demonstrated that higher proportions of slow wave sleep (N3) were protective for the development of type 2 diabetes. Recent animal and human studies also point to the effects of sleep micro-architecture—specifically the coupling of slow waves and spindles- on short-term and long-term glucose regulation, possibly through the effects on signaling between the hippocampus and hypothalamus, and changes in autonomic nervous system output. Experimental data also demonstrate a prominent role of the circadian system in regulating glucose and lipid levels. In support of those studies, epidemiological associations have identified significant associations between actigraphy-based measures of sleep irregularity (a marker of circadian disruption) with incident metabolic dysfunction and hypertension. This rich data implicating sleep disturbances as drivers of metabolic disease, coupled with data indicating a high prevalence of sleep and circadian disorders in the population, suggest novel opportunities to target sleep and circadian pathways for preventing or treating metabolic dysfunction, as well as key knowledge gaps.
The National Sleep Research Resource (NSRR; sleepdata.org) provides a large and growing repository of well-annotated polysomnograms (PSGs), actigraphy studies, and questionnaires, some associated with clinical and biochemical data relevant to understanding the links between sleep and circadian disorders with metabolic disease. Notably, the NSRR includes over 50,000 PSGs, which concurrently include multiple physiological signals with high temporal resolution, allowing generation of thousands of variables summarizing dynamic physiological changes and “cross-talk” between physiological systems...(Please see https://dknet.org/about/blog/2674 for full abstract)
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Office Hours - "Are You Ready for 2023: New NIH Data Management and Sha...
For all proposals submitted on/after January 25 2023, NIH will require the sharing of data from all NIH funded studies. Do you have appropriate data management practices and sharing plans in place to meet these requirements? Have questions or need some help? Join the dkNET office hours to learn about NIH’s policy (NOT-OD-21-013) and resources that could help.
*Previous Office Hours Slides and Recording: https://dknet.org/rin/research-data-management
Upcoming Webinars Schedule: https://dknet.org/about/webinar
dkNET Webinar: Leveraging Computational Strategies to Identify Type 1 Diabete...
dkNET New Investigator Pilot Program in Bioinformatics Awardee Webinar Series
Presenter: Wenting Wu, PhD. Research Assistant Professor, Center for Diabetes and Metabolic Diseases, Department of Medical and Molecular Genetics, Associate Director of Data and Analytics Core for Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine
Abstract
Type 1 diabetes (T1D) is an immune-mediated disease that results in insulin insufficiency and affects 0.3% of the population, including both children and adults. To support clinical trial efforts, there is an urgent need to develop reliable biomarkers capable of predicting T1D risk and guiding therapeutic interventions. Recently, whole blood bulk RNA sequencing has been used to guide T1D clinical trial design and assess response to disease modifying interventions. While the use of bulk RNA sequencing is cost-effective, these datasets provide limited information about cell specific gene expression changes. Here, we aimed to apply computational strategies to deconvolute cell type composition using cell specific gene expression references. Single-cell RNA sequencing (scRNA-seq) was conducted to profile peripheral blood mononuclear cells obtained from youth within recent T1D onset and age- and sex-matched controls and identified 31 distinct cell clusters. Using this pre-defined reference dataset, we ran computational algorithms CIBERSORTx and other deconvolution methods simultaneously to deconvolute cell proportions using public clinical trial data. We focused our initial analysis on data from the TN-20 Rituximab trial, which tested the anti-CD20 monoclonal antibody rituximab vs placebo in recent onset T1D. This talk will introduce recent advances of scRNA-seq techniques and computational deconvolution methods and demonstrate that how we apply different deconvolution approaches for secondary analysis of existing clinical trial data, in the purpose of linking cell specific immune signatures associated with drug responder status.
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar: Estimating Relative Beta-Cell Function During Continuous Gluco...
dkNET New Investigator Pilot Program in Bioinformatics Awardee Webinar Series
Presenter: Joon Ha, PhD. Associate Professor, Department of Mathematics, Howard University, Washington DC.
Abstract
The most common form of diabetes, type 2 diabetes (T2D) is a failure of insulin-secreting pancreatic beta-cells to increase insulin to the level required to maintain normal blood glucose. Thus, identifying beta-cell function and insulin sensitivity in those who are at high risk is crucial to preventing and delaying the disease. Hyper-glycemic clamp and euglycemic hyper- insulinemic clamp are considered to be gold standard measures for these quantities. However, these two methods demand highly skilled labor and thus are cost-prohibitive. Glucose challenge tests have been used to estimate beta-cell function and insulin sensitivity. The product of beta-cell function and insulin sensitivity, termed the disposition index (DI), is of great value because it measures beta-cell function relative to insulin requirements. However, glucose challenge tests are expensive and time-consuming and therefore impractical to implement in large-scale clinical studies. To address this challenge, we developed a model disposition index (mDI estimated without insulin) that does not require insulin measurements during an oral glucose tolerance test (OGTT) (Ha et al., Diabetes 2021 (70) suppl. 1). mDI outperforms the conventional oral disposition index (oDI) at predicting progression to diabetes.
To further increase access and refine the assessments of beta-cell function, we are adapting our model to calculate a model disposition index using continuous glucose monitoring (CGM). CGM has been in the spotlight of diabetes management and has revolutionized the field of medicine as they are approved for glucose monitoring and clinical decision-making in patients with diabetes. CGM devices are relatively inexpensive compared to oral glucose challenge tests, accessible, and simple to use, especially in remote or free-living environments. The CGM device continuously measures interstitial glucose every 5 minutes and provides glucose profiles for 7-14 days. Thus, there are numerous data points compared to glucose challenge tests, but the abundant data points have not previously been used for estimating metabolic parameters. We compared mDI to two widely used CGM-derived metabolic parameters for assessing metabolic status and risk, mean glucose and glycemic excursion. Both mean glucose and glycemic excursion correlated strongly with mDI. The new approach promises to be cost- effective and easy to perform and therefore implementable in large-scale clinical studies. As for specific clinical applications, estimated model parameters during OGTTs identified ethnic differences in common pathways to T2D between Pima Indians and Koreans.
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar: Postpartum Glucose Screening Among Homeless Women with Gestati...
dkNET New Investigator Pilot Program in Bioinformatics Awardee Webinar Series
Presenter: Rie Sakai-Bizmark, PhD. Assistant Professor, The Lundquist Institute at Harbor-UCLA Medical Center, David Geffen School of Medicine at UCLA
Abstract
Women with gestational diabetes mellitus (GDM) are at high risk of developing glucose intolerance after delivery. In the long term, women with GDM have a nearly 10-fold higher risk of developing type 2 diabetes mellitus (T2D) than women without GDM. The American Diabetes Association (ADA) and the American College of Obstetrics and Gynecology (ACOG) recommend that women with GDM undergo a 75-g oral glucose tolerance test (OGTT) between four and 12 weeks postpartum, and periodically thereafter. However, postpartum glucose screening (PGS) rate is historically low despite of various interventions to improve such rate. We hypothesized that PGS rate is lower among postpartum homeless women than their housed counterparts, and that interventions to improve PGS rate among postpartum homeless women with GDM should be tailored to their unique circumstances. The Japanese Society of Diabetes and Pregnancy (JSDP) modified the method to perform PGS with random plasma glucose (RPG) and glycated hemoglobin (HbA1c), which are simple and less invasive, to reduce the risk of COVID-19 infection by shortening the time spent in the hospital. RPG or HbA1c test do not require fasting. Therefore, homeless women who utilized care for other reasons could have the test as PGS. Given the barriers faced by homeless individuals, we hypothesize that RPG and HbA1c at healthcare utilizations during the postpartum period could be one of the strategies to identify high-risk individuals early because 1] healthcare utilizations are an opportunity for healthcare providers and social workers to educate homeless patients on GDM and their insurance eligibility and coverage for the screening, and 2] the physical barriers to health care access, which are often cited as a reason for the low PGS rate, are removed.
This proposed study will use administrative data from five states (AZ, CO, NC, NJ, and OR), which collectively include 9.3% of the US female homeless population. Each state will provide detailed, linked, multi-level, anonymized data for postpartum homeless women from four sources: 1] Medicaid claims; 2] Homeless Management Information System (HMIS); 3] birth records; and 4] the American Hospital Association (AHA) database to obtain hospital characteristics. With data from 2013 to 2020, an estimated sample size of 24,000 homeless women who delivered babies and 3,290 postpartum homeless women with GDM will be included.
First, we will estimate rates of GDM and PGS among homeless women. Second, we will estimate the cost-effectiveness of performing RPG and HbA1c tests...[Full abstract: https://dknet.org/about/blog/2581]
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar: Choosing Sample Sizes for Multilevel and Longitudinal Studies ...
dkNET Webinar: Choosing Sample Sizes for Multilevel and Longitudinal Studies Analyzed with Linear Mixed Models
Presenter:
Kylie K. Harrall, MS, Research Instructor, Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus
Abstract
Planning a reproducible study requires selecting a sample size which will ensure appropriate statistical power. Free point-and-click software (Kreidler et al., Journal of Statistical Software, 2013, 10.18637/jss.v054.i10) makes it easy to select a sample size for clustered and longitudinal designs with linear mixed models. The software, a suite of training modules, and reference materials are freely available online (www.SampleSizeShop.org ). The software interface and training materials are aimed at biomedical scientists, included those funded by NIDDK. We give examples of study designs for which the software will compute power and sample size, including a study with clustering, a study with longitudinal repeated measures, and a study with multiple outcomes, where heterogeneity of response among subgroups is of interest.
The top 3 key questions that the Sample Size Shop can answer:
1. What free, online, point-and-click, wizard-style, NIH-funded, validated, published power and sample size software provides calculations for studies with clusters, longitudinal studies, and longitudinal studies with clusters?
2. Can GLIMMPSE (www.SampleSizeShop.org) compute power and sample size for randomized controlled clinical trials and observational studies funded by NIDDK?
3. Why use validated power and sample size software instead of writing simulations?
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar: : FAIR Data Curation of Antibody/B-cell and T-cell Receptor Se...
Abstract
AIRR-seq data (antibody/B-cell and T-cell receptor sequences from Adaptive Immune Receptor Repertoires) can describe the adaptive immune response in exquisite detail, and comparison and analysis of these data across studies and institutions can greatly contribute to the development of diagnostics and therapeutics, including the discovery of monoclonal antibodies for treatment of autoimmune diseases.
The AIRR community has developed protocols and standards for curating, analyzing and sharing AIRR-seq data (www.airr-community.org), and supports the AIRR Data Commons, a set of geographically distributed repositories that follows the AIRR Community’s metadata standards and the FAIR principles. The ADC currently comprises > 5 Bn receptor sequences from over 86 studies and ~9000 repertoires. The data model of the ADC has recently been expanded to include gene expression and cell phenotype data from single immune receptor cells, as well as MHC/HLA genotyping.
The iReceptor Gateway (ireceptor.org) queries this AIRR Data Commons for specific “metadata”, e.g. “find all repertoires from T1D studies” or for specific CDR3 sequences (e.g., find all repertoires from healthy individuals expressing this CDR3 sequence). Data from these federated repositories can then be analyzed through the Gateway by several sophisticated analysis tools, or downloaded for further analysis offline. The iReceptor Team at Simon Fraser University has recently initiated a collaboration to greatly expand the amount of bulk and single-cell immune profiling data from T1D studies in the AIRR Data Commons. For more information on obtaining or sharing AIRR-seq data contact support@ireceptor.org.
The top 3 key questions that the Adaptive Immune Receptor Repertoire (AIRR) can answer:
1. A researcher observes that many individuals with Type 1 Diabetes express a specific B-cell or T-cell receptor compared to controls (i.e., a “public” clonotype). To what degree is this receptor observed to be public across other T1D studies or other autoimmune disease populations?
2. Can Machine Learning be used to identify individuals who will respond well to a new cancer immunotherapy based on differences in their antibody/B-cell or T-cell receptor repertoires as curated in the AIRR Data Commons?
3. Is there an association between particular HLA, immunoglobulin (IG), or T-cell receptor (TR) germline gene polymorphisms and propensity toward specific infectious or autoimmune diseases?
Presenters:
Dr. Felix Breden, Scientific Director, iReceptor
Dr. Brian Corrie, Technical Director, iReceptor
Dr. Kira Neller, Bioinformatics Director, iReceptor
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Office Hours - "Are You Ready for 2023? New NIH Data Management and Sha...
For all proposals submitted on/after January 25 2023, NIH will require the sharing of data from all NIH funded studies. Do you have appropriate data management practices and sharing plans in place to meet these requirements? Have questions or need some help? Join the dkNET office hours to learn about NIH’s policy (NOT-OD-21-013) and resources (https://dknet.org/rin/research-data-management) that could help.
Upcoming Webinars Schedule: https://dknet.org/about/webinar
dkNET Webinar "The Mission and Progress of the(sugar)science: Helping Scienti...
Abstract
The(sugar)science was launched two years ago with the aim of helping scientists who study type 1 diabetes (T1D) and related interdisciplinary fields connect globally. We also wanted to create a digital space where trainees in the field can be supported, celebrated and connected to future positions. As part of our mission, our all volunteer team created the State of the Science series (2021. 2022), connecting global thought leaders around T1D research topics for discussion with a larger scientific audience. The second State of Science series was led by women scientists following the ADA publication which highlighted the paucity of women scientists in the leadership positions in the field.
To encourage the scientific community at large to dive into pre-existing data and pull out novel hypotheses that pertain to T1D, we created and together with dkNET, hosted D-Challenge 2021 and 2022. These competitions awarded $40K and $50K respectively to those who mined data and developed the most creative and testable hypothesis as judged by scientific experts in the field. These teams were also able to have an audience with the JDRFT1D Fund as part of a "pitch polish" which facilitated their interaction with venture capital.
To date, we have hosted over 200 interviews with T1D focused scientists in academia and industry and have an audience of 35K. Our reach on social media continues to grow and our metrics indicate a robust following. We share opportunities for positions in the field, engage and support trainees and together, our young scientific team published a paper, Similarities between bacterial GAD and human GAD65: Implications in gut mediated autoimmune type 1 diabetes, PLOS, February 2022.
We are currently engaged in the build of a T1D TCR Repository. We connected the AIRR data commons community with top TCR scientists in the field to begin this community based venture. It has the possibility to be incredibly instructive in defining the prodrome , which will further inform the field as it pertains to understanding the etiology of T1D.
Current team members that will join the discussion today will be Neha Mejety, Johns Hopkins University undergraduate and Tiffany Richardson, doctoral degree candidate at VUMC Diabetes.
The top 3 key questions that the(sugar)science can answer:
1. How can I find scientists to collaborate with in Type 1 diabetes research?
2. Where can I learn about Type 1 diabetes trending topics?
3. Where can I find forums to discuss novel ideas with scientists or key opinion leaders and find opportunities for Type 1 diabetes research ?
Presenters:
Monica Westley, PhD, Founder, the(sugar)science
Tiffany Richardson
Neha Majety
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar: The Human BioMolecular Atlas Program (HuBMAP) 10/14/2022
Abstract
HuBMAP aims to catalyze the development of an open, global framework for comprehensively mapping the human body at cellular resolution. HuBMAP goals include: (1) Accelerate the development of the next generation of tools and techniques for constructing high resolution spatial tissue maps. (2) Generate foundational 3D tissue atlases. (3) Establish an open data platform. (4) Coordinate and collaborate with other funding agencies, programs, and the biomedical research community. (5) Support projects that demonstrate the value of the resources developed by the program. The HuBMAP Portal can be found at https://portal.hubmapconsortium.org and the Visible Human MOOC describes the compilation and coverage of HuBMAP data, demonstrates new single-cell analysis and mapping techniques, and introduces major features of the HuBMAP portal.
The top 3 key questions that HuBMAP can answer:
1. What assay types are best to map the human body in 3D and across scales?
2. What Common Coordinate System (CCF) is best to construct the Human Reference Atlas?
3. How can others help construct and/or use the Human Reference Atlas?
Presenters:
Katy Börner, PhD, Victor H. Yngve Distinguished Professor of Engineering and Information Science, Department of Intelligent Systems Engineering and Information Science, Indiana University
Jeffrey Spraggins, PhD, Assistant Professor, Department of Cell and Developmental Biology, Vanderbilt University
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar "Visualizing Organelle and Cell Longevity In Situ" 05/20/22
Presenter: Rafael Arrojo e Drigo, Ph.D. Assistant Professor, Department of Molecular Physiology and Biophysics, Vanderbilt University
Abstract
Cells in largely post-mitotic organs can be as old as their host organism. These long-lived cells (LLCs) face a lifelong demand for performance to maintain organ function and are constantly exposed to drivers of molecular and cellular damage. Accordingly, dysfunction of LLCs is associated with aging and age-associated disease processes. Understanding cellular longevity mechanisms requires the identity and distribution pattern of LLCs. We developed imaging tools to quantify the age of cells in situ, which led to the discovery of new LLC types throughout the mouse body. This includes different cell types in the pancreas, where most beta cells can be as old as neurons in the brain. In this presentation, I will show how we apply different microscopy tools to bridge spatial and temporal scales in biology to quantify protein complex, organelle, and cell age in tissues. Applicable to virtually any cell, this imaging platform can reveal the temporal dynamics and longevity of structural components in vivo and their contribution to cell and tissue organization and function.
Upcoming webinars schedule: https://dknet.org/about/webinar
dkNET Webinar "Integrative Artificial Intelligence Approach to Predict T1D" 0...
Presenter: Kenneth Young, Ph.D. Assistant Professor, Health Informatics Institute, University of South Florida
Abstract
Type 1 diabetes (T1D) is a complex and heterogenous autoimmune disease that is no longer considered a clear-cut clinically diagnosed disease. T1D is multifaceted and the efficacy of therapeutic interventions varies greatly. With the evidence of etiological differences in T1D and the availability of high-dimensional multi-omics data in combination with clinical and environmental data, this project aims to use an artificial intelligence (AI) exploratory approach that may aid in the identification of new markers to predict IA and T1D.
This project utilizes data from NIDDK funded by The Environmental Determinants of Diabetes in the Young (TEDDY) study. TEDDY has generated over 900TB of diverse data types including multi-omics data, deep phenotyping, and environmental factor measurements every three-six months for fifteen years. We utilize deep learning methods, such as convolutional neural networks (CNN) and recurrent neural networks (RNN) that apply bidirectional long short-term memory (LSTM), in combination with multi-layer perceptron (MLP), to evaluate the prediction of IA and T1D. To aid in T1D predication, this project uses innovative and transformative AI approaches that combine temporal and static data, which may ultimately provide insights into the complex heterogeneity, diversity, and pathogenesis of T1D. The knowledge gained from this project may not only help advance the T1D community, but may have a broad impact on a variety of autoimmune diseases such as celiac and thyroid diseases which frequently coexist and share genetic susceptibility to T1D.
Plus de dkNET (20)
dkNET Webinar: The 4DN Data Portal - Data, Resources and Tools to Help Elucid...
dkNET Webinar: The 4DN Data Portal - Data, Resources and Tools to Help Elucid...
dkNET Webinar "Texera: A Scalable Cloud Computing Platform for Sharing Data a...
dkNET Webinar "Texera: A Scalable Cloud Computing Platform for Sharing Data a...
dkNET Webinar: Unlocking the Power of FAIR Data Sharing with ImmPort 04/12/2024
dkNET Webinar: Unlocking the Power of FAIR Data Sharing with ImmPort 04/12/2024
dkNET Webinar "The Multi-Omic Response to Exercise Training Across Rat Tissue...
dkNET Webinar "The Multi-Omic Response to Exercise Training Across Rat Tissue...
dkNET Webinar: The Collaborative Microbial Metabolite Center – Democratizing ...
dkNET Webinar: The Collaborative Microbial Metabolite Center – Democratizing ...
dkNET Webinar: An Encyclopedia of the Adipose Tissue Secretome to Identify Me...
dkNET Webinar: An Encyclopedia of the Adipose Tissue Secretome to Identify Me...
dkNET Webinar: A Single Cell Atlas of Human and Mouse White Adipose Tissue 11...
dkNET Webinar: A Single Cell Atlas of Human and Mouse White Adipose Tissue 11...
dkNET Webinar "The National Sleep Research Resource (NSRR) - Opportunities fo...
dkNET Webinar "The National Sleep Research Resource (NSRR) - Opportunities fo...
dkNET Office Hours - "Are You Ready for 2023: New NIH Data Management and Sha...
dkNET Office Hours - "Are You Ready for 2023: New NIH Data Management and Sha...
dkNET Webinar: Leveraging Computational Strategies to Identify Type 1 Diabete...
dkNET Webinar: Leveraging Computational Strategies to Identify Type 1 Diabete...
dkNET Webinar: Estimating Relative Beta-Cell Function During Continuous Gluco...
dkNET Webinar: Estimating Relative Beta-Cell Function During Continuous Gluco...
dkNET Webinar: Postpartum Glucose Screening Among Homeless Women with Gestati...
dkNET Webinar: Postpartum Glucose Screening Among Homeless Women with Gestati...
dkNET Webinar: Choosing Sample Sizes for Multilevel and Longitudinal Studies ...
dkNET Webinar: Choosing Sample Sizes for Multilevel and Longitudinal Studies ...
dkNET Webinar: : FAIR Data Curation of Antibody/B-cell and T-cell Receptor Se...
dkNET Webinar: : FAIR Data Curation of Antibody/B-cell and T-cell Receptor Se...
dkNET Office Hours - "Are You Ready for 2023? New NIH Data Management and Sha...
dkNET Office Hours - "Are You Ready for 2023? New NIH Data Management and Sha...
dkNET Webinar "The Mission and Progress of the(sugar)science: Helping Scienti...
dkNET Webinar "The Mission and Progress of the(sugar)science: Helping Scienti...
dkNET Webinar: The Human BioMolecular Atlas Program (HuBMAP) 10/14/2022
dkNET Webinar: The Human BioMolecular Atlas Program (HuBMAP) 10/14/2022
dkNET Webinar "Visualizing Organelle and Cell Longevity In Situ" 05/20/22
dkNET Webinar "Visualizing Organelle and Cell Longevity In Situ" 05/20/22
dkNET Webinar "Integrative Artificial Intelligence Approach to Predict T1D" 0...
dkNET Webinar "Integrative Artificial Intelligence Approach to Predict T1D" 0...
Dernier
Applied Science: Thermodynamics, Laws & Methodology.pdf
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
The binding of cosmological structures by massless topological defects
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
Authoring a personal GPT for your research and practice: How we created the Q...
Thematic analysis in qualitative research is a time-consuming and systematic task, typically done using teams. Team members must ground their activities on common understandings of the major concepts underlying the thematic analysis, and define criteria for its development. However, conceptual misunderstandings, equivocations, and lack of adherence to criteria are challenges to the quality and speed of this process. Given the distributed and uncertain nature of this process, we wondered if the tasks in thematic analysis could be supported by readily available artificial intelligence chatbots. Our early efforts point to potential benefits: not just saving time in the coding process but better adherence to criteria and grounding, by increasing triangulation between humans and artificial intelligence. This tutorial will provide a description and demonstration of the process we followed, as two academic researchers, to develop a custom ChatGPT to assist with qualitative coding in the thematic data analysis process of immersive learning accounts in a survey of the academic literature: QUAL-E Immersive Learning Thematic Analysis Helper. In the hands-on time, participants will try out QUAL-E and develop their ideas for their own qualitative coding ChatGPT. Participants that have the paid ChatGPT Plus subscription can create a draft of their assistants. The organizers will provide course materials and slide deck that participants will be able to utilize to continue development of their custom GPT. The paid subscription to ChatGPT Plus is not required to participate in this workshop, just for trying out personal GPTs during it.
Katherine Romanak - Geologic CO2 Storage.pdf
Presented at June 6-7 Texas Alliance of Groundwater Districts Business Meeting
11.1 Role of physical biological in deterioration of grains.pdf
Storagedeteriorationisanyformoflossinquantityandqualityofbio-materials.
Themajorcausesofdeteriorationinstorage
•Physical
•Biological
•Mechanical
•Chemical
Storageonlypreservesquality.Itneverimprovesquality.
Itisadvisabletostartstoragewithqualityfoodproduct.Productwithinitialpoorqualityquicklydepreciates
Pests of Storage_Identification_Dr.UPR.pdf
InIndia-post-harvestlosses-unscientificstorage,insects,rodents,micro-organismsetc.,accountforabout10percentoftotalfoodgrains
Graininfestation
Directdamage
Indirectly
•theexuviae,skin,deadinsects
•theirexcretawhichmakefoodunfitforhumanconsumption
About600speciesofinsectshavebeenassociatedwithstoredgrainproducts
100speciesofinsectpestsofstoredproductscauseeconomiclosses
SAR of Medicinal Chemistry 1st by dk.pdf
In this presentation include the prototype drug SAR on thus or with their examples .
Syllabus of Second Year B. Pharmacy
2019 PATTERN.
Bob Reedy - Nitrate in Texas Groundwater.pdf
Presented at June 6-7 Texas Alliance of Groundwater Districts Business Meeting
The debris of the ‘last major merger’ is dynamically young
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...
(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...Scintica Instrumentation
Targeting Hsp90 and its pathogen Orthologs with Tethered Inhibitors as a Diagnostic and Therapeutic Strategy for cancer and infectious diseases with Dr. Timothy Haystead.Randomised Optimisation Algorithms in DAPHNE
Slides from talk:
Aleš Zamuda: Randomised Optimisation Algorithms in DAPHNE .
Austrian-Slovenian HPC Meeting 2024 – ASHPC24, Seeblickhotel Grundlsee in Austria, 10–13 June 2024
https://ashpc.eu/
waterlessdyeingtechnolgyusing carbon dioxide chemicalspdf
The technology uses reclaimed CO₂ as the dyeing medium in a closed loop process. When pressurized, CO₂ becomes supercritical (SC-CO₂). In this state CO₂ has a very high solvent power, allowing the dye to dissolve easily.
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters
represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions
among stars.
Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate
the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars.
The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun.
Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically,
the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec.
Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within
and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation
were carried out using the ACIS-Extract software.
Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a
photon flux threshold of approximately 2 × 10−8 photons cm−2
s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
Sharlene Leurig - Enabling Onsite Water Use with Net Zero Water
Sharlene Leurig - Enabling Onsite Water Use with Net Zero WaterTexas Alliance of Groundwater Districts
Presented at June 6-7 Texas Alliance of Groundwater Districts Business MeetingMending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Ozturkcan, S., Berndt, A., & Angelakis, A. (2024). Mending clothing to support sustainable fashion. Presented at the 31st Annual Conference by the Consortium for International Marketing Research (CIMaR), 10-13 Jun 2024, University of Gävle, Sweden.
Equivariant neural networks and representation theory
Or: Beyond linear.
Abstract: Equivariant neural networks are neural networks that incorporate symmetries. The nonlinear activation functions in these networks result in interesting nonlinear equivariant maps between simple representations, and motivate the key player of this talk: piecewise linear representation theory.
Disclaimer: No one is perfect, so please mind that there might be mistakes and typos.
dtubbenhauer@gmail.com
Corrected slides: dtubbenhauer.com/talks.html
Dernier (20)
GBSN - Biochemistry (Unit 6) Chemistry of Proteins
GBSN - Biochemistry (Unit 6) Chemistry of Proteins
Applied Science: Thermodynamics, Laws & Methodology.pdf
Applied Science: Thermodynamics, Laws & Methodology.pdf
The binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defects
Authoring a personal GPT for your research and practice: How we created the Q...
Authoring a personal GPT for your research and practice: How we created the Q...
11.1 Role of physical biological in deterioration of grains.pdf
11.1 Role of physical biological in deterioration of grains.pdf
The debris of the ‘last major merger’ is dynamically young
The debris of the ‘last major merger’ is dynamically young
(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...
(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...
waterlessdyeingtechnolgyusing carbon dioxide chemicalspdf
waterlessdyeingtechnolgyusing carbon dioxide chemicalspdf
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
Sharlene Leurig - Enabling Onsite Water Use with Net Zero Water
Sharlene Leurig - Enabling Onsite Water Use with Net Zero Water
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Equivariant neural networks and representation theory
Equivariant neural networks and representation theory
dkNET Webinar: dkNET Hypothesis Center Live Demo 09/24/2021
- 1. An NIDDK Resource dknet.org dkNET Hypothesis Center: Making Bioinformatics Tools Accessible dkNET Webinar September 24, 2021
- 2. An NIDDK Resource dknet.org About dkNET • Research resource information portal for biomedical researchers • Information network to connect DK researchers and NIH-funded resources • Funded by National Institute of Health (NIH) - National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) • Developed and maintained by the FAIR Data Informatics Laboratory (fdilab.org) at UCSD (Supports major informatics projects in biomedicine)
- 3. An NIDDK Resource dknet.org ○ Resource Reports: helps researchers find and evaluate resources ○ Authentication Reports: assists researchers in preparing NIH authentication plans ○ FAIR Data Services: assists researchers in finding data repositories and standards for preparing data management plans ○ Discovery Portal: connects researchers to more than 200 biomedical databases ○ Hypothesis Center: analyze and explore diverse data to generate or test research hypotheses 5 AREAS IN THE PORTAL https://www.youtube.com/channel/UCwukSrB8L61Fhwjv3x20lOQ/playlists
- 4. An NIDDK Resource dknet.org How Can dkNET Help Researchers? Construct a hypothesis Ask a question Do background research Plan experiments Collect and analyze data Publish results Discovery Portal Hypothesis Center Resource Reports Authentication Reports Information Material Data Tools Funded grant and funding opportunities Literature Tutorials Resource Reports Hypothesis Center FAIR Data Resources Data Management Data Repositories Resource Reports Cite RRID Track Resources Resource Identification Authentication plans NIH Mandates on Rigor and Reproducibility for grant submission
- 5. Significant growth of available data and online tools and resources
- 6. An NIDDK Resource dknet.org dkNET Portal dknet.org
- 7. An NIDDK Resource dknet.org Stories of Discovery
- 8. An NIDDK Resource dknet.org Stories of Discovery
- 9. An NIDDK Resource dknet.org Launch Tutorials
- 10. An NIDDK Resource dknet.org Selecting a Tutorial
- 11. An NIDDK Resource dknet.org Hypothesis Center Tutorials
- 12. An NIDDK Resource dknet.org Tutorial Overview
- 13. An NIDDK Resource dknet.org Learning Goals
- 14. An NIDDK Resource dknet.org Detailed Tutorial
- 15. An NIDDK Resource dknet.org Finishing Tutorial
- 16. An NIDDK Resource dknet.org Linking Multiple Tools / Resources
- 17. An NIDDK Resource dknet.org Interactive Tutorial Launch Next Tutorial
- 18. An NIDDK Resource dknet.org Resource Overview
- 19. An NIDDK Resource dknet.org Integrate with Resource Reports
- 20. An NIDDK Resource dknet.org External Tutorials
- 21. An NIDDK Resource dknet.org
- 22. An NIDDK Resource dknet.org Informational Content
- 23. An NIDDK Resource dknet.org Bioinformatics Tool Overview
- 24. An NIDDK Resource dknet.org Bioinformatics Resource Overview
- 25. An NIDDK Resource dknet.org Resource Overview
- 26. An NIDDK Resource dknet.org Resources Overview
- 27. An NIDDK Resource dknet.org Tutorial Overview
- 28. An NIDDK Resource dknet.org How Can You Contribute... ● Suggestions of online tools and resources ● Suggestions of use cases ○ multi-resource tutorials ● Information on tutorials that already exist ● Contribute stories of discovery ● Develop tutorials within the Hypothesis Center info@dknet.org
- 29. An NIDDK Resource dknet.org