Evidence map›Paper›PMID 26393351›Full record

ArticlePloS one2015

The NIDDK Information Network: A Community Portal for Finding Data, Materials, and Tools for Researchers Studying Diabetes, Digestive, and Kidney Diseases.

Patricia L Whetzel, Jeffrey S Grethe, Davis E Banks, Maryann E Martone

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. D2H2: diabetes data and hypothesis hub.Bioinformatics advances · 2023
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. DataMed - an open source discovery index for finding biomedical datasets.Journal of the American Medical Informatics Association : JAMIA · 2018
    Article
  12. Article
  13. Improving the discoverability, accessibility, and citability of omics datasets: a case report.Journal of the American Medical Informatics Association : JAMIA · 2017
    Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Patricia L WhetzelCenter for Research in Biological Systems, University of California, San Diego, San Diego, California, United States of America.
Jeffrey S GretheCenter for Research in Biological Systems, University of California, San Diego, San Diego, California, United States of America.
Davis E BanksCenter for Research in Biological Systems, University of California, San Diego, San Diego, California, United States of America.
Maryann E MartoneCenter for Research in Biological Systems, University of California, San Diego, San Diego, California, United States of America; Dept of Neurosciences, University of California, San Diego, San Diego, California, United States of America.

Funding

NIDDK Network Coordinating UnitU24DK097771 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Shuibing Chen, Jeffrey S. Grethe · 2013 to 2026
$20.9M
NIDDK NIH HHS 5 U24 DK097771NIDDK NIH HHS U24 DK097771
6 · The paper itself

Abstract

The NIDDK Information Network (dkNET; http://dknet.org) was launched to serve the needs of basic and clinical investigators in metabolic, digestive and kidney disease by facilitating access to research resources that advance the mission of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). By research resources, we mean the multitude of data, software tools, materials, services, projects and organizations available to researchers in the public domain. Most of these are accessed via web-accessible databases or web portals, each developed, designed and maintained by numerous different projects, organizations and individuals. While many of the large government funded databases, maintained by agencies such as European Bioinformatics Institute and the National Center for Biotechnology Information, are well known to researchers, many more that have been developed by and for the biomedical research community are unknown or underutilized. At least part of the problem is the nature of dynamic databases, which are considered part of the "hidden" web, that is, content that is not easily accessed by search engines. dkNET was created specifically to address the challenge of connecting researchers to research resources via these types of community databases and web portals. dkNET functions as a "search engine for data", searching across millions of database records contained in hundreds of biomedical databases developed and maintained by independent projects around the world. A primary focus of dkNET are centers and projects specifically created to provide high quality data and resources to NIDDK researchers. Through the novel data ingest process used in dkNET, additional data sources can easily be incorporated, allowing it to scale with the growth of digital data and the needs of the dkNET community. Here, we provide an overview of the dkNET portal and its functions. We show how dkNET can be used to address a variety of use cases that involve searching for research resources.

Indexed as

Information ServicesAnimalsDatabases, FactualDiabetes MellitusDigestive System DiseasesHumansKidney DiseasesModels, AnimalNational Institute of Diabetes and Digestive and Kidney Diseases (U.S.)ResearchSearch EngineUnited States

Identifiers

PMID26393351
PMCPMC4578941

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.