Evidence map›Paper›PMID 34433410›Full record

ArticleBMC bioinformatics2021

LinkedImm: a linked data graph database for integrating immunological data.

Syed Ahmad Chan Bukhari, Shrikant Pawar, Jeff Mandell, Steven H Kleinstein, Kei-Hoi Cheung

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Syed Ahmad Chan BukhariDivision of Computer Science, Mathematics and Science, Collins College of Professional Studies, St. John's University, New York, NY, USA.
Shrikant PawarDepartment of Genetics, Yale School of Medicine, New Haven, CT, USA.
Jeff MandellProgram in Computational Biology and Bioinformatics, Yale School of Medicine, New Haven, CT, USA.
Steven H KleinsteinProgram in Computational Biology and Bioinformatics, Yale School of Medicine, New Haven, CT, USA.
Kei-Hoi CheungProgram in Computational Biology and Bioinformatics, Yale School of Medicine, New Haven, CT, USA. kei.cheung@yale.edu.

Funding

Semantic Integration of ImmPort and the Linked Data Cloud for Systems VaccinologyUH2AI132341 · NIAID · YALE UNIVERSITY · PI KLEINSTEIN, STEVEN H. · 2017 to 2018
$461k
NIAID NIH HHS UH2 AI132341
6 · The paper itself

Abstract

backgroundMany systems biology studies leverage the integration of multiple data types (across different data sources) to offer a more comprehensive view of the biological system being studied. While SQL (Structured Query Language) databases are popular in the biomedical domain, NoSQL database technologies have been used as a more relationship-based, flexible and scalable method of data integration.

resultsWe have created a graph database integrating data from multiple sources. In addition to using a graph-based query language (Cypher) for data retrieval, we have developed a web-based dashboard that allows users to easily browse and plot data without the need to learn Cypher. We have also implemented a visual graph query interface for users to browse graph data. Finally, we have built a prototype to allow the user to query the graph database in natural language.

conclusionWe have demonstrated the feasibility and flexibility of using a graph database for storing and querying immunological data with complex biological relationships. Querying a graph database through such relationships has the potential to discover novel relationships among heterogeneous biological data and metadata.

Indexed as

Information Storage and RetrievalSemantic WebDatabases, FactualLanguageSystems BiologyGraph databaseImmunologyInfluenza vaccineKnowledgebaseOntology

Identifiers

PMID34433410
PMCPMC8385794

What Socratic 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 Socratic graph.