Evidence map›Paper›PMID 18605991›Full record

ArticleBMC genomics2008

T2D-Db: an integrated platform to study the molecular basis of Type 2 diabetes.

Shipra Agrawal, Nevenka Dimitrova, Prasanthi Nathan, K Udayakumar, S Sai Lakshmi, S Sriram, N Manjusha, Urmi Sengupta

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
0.8field-weighted citation impact, top 27% of its field
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

18 citing papers in PubMed, 41 citations in OpenAlex.

  1. DiabetesOmic: A comprehensive multi-omics diabetes database.Computational and structural biotechnology journal · 2025
    Article
  2. Review
  3. On building a diabetes centric knowledge base via mining the web.BMC medical informatics and decision making · 2019
    Article
  4. Article
  5. Article
  6. Genetic variants inExperimental and therapeutic medicine · 2017
    Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. T-HOD: a literature-based candidate gene database for hypertension, obesity and diabetes.Database : the journal of biological databases and curation · 2013
    Article
  15. Article
  16. Article
  17. Article
  18. Review
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

8 authors at 2 institutions in 1 country.

Shipra AgrawalInstitute of Bioinformatics and Applied Biotechnology, Bangalore, India. shipra@ibab.ac.in
Nevenka Dimitrova
Prasanthi Nathan
K Udayakumar
S Sai Lakshmi
S Sriram
N Manjusha
Urmi Sengupta
Institute of Bioinformatics and Applied Biotechnology · INPhilips (India) · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundType 2 Diabetes Mellitus (T2DM) is a non insulin dependent, complex trait disease that develops due to genetic predisposition and environmental factors. The advanced stage in type 2 diabetes mellitus leads to several micro and macro vascular complications like nephropathy, neuropathy, retinopathy, heart related problems etc. Studies performed on the genetics, biochemistry and molecular biology of this disease to understand the pathophysiology of type 2 diabetes mellitus has led to the generation of a surfeit of data on candidate genes and related aspects. The research is highly progressive towards defining the exact etiology of this disease.

resultsT2D-Db (Type 2 diabetes Database) is a comprehensive web resource, which provides integrated and curated information on almost all known molecular components involved in the pathogenesis of type 2 diabetes mellitus in the three widely studied mammals namely human, mouse and rat. Information on candidate genes, SNPs (Single Nucleotide Polymorphism) in candidate genes or candidate regions, genome wide association studies (GWA), tissue specific gene expression patterns, EST (Expressed Sequence Tag) data, expression information from microarray data, pathways, protein-protein interactions and disease associated risk factors or complications have been structured in this on line resource.

conclusionInformation available in T2D-Db provides an integrated platform for the better molecular level understanding of type 2 diabetes mellitus and its pathogenesis. Importantly, the resource facilitates graphical presentation of the gene/genome wide map of SNP markers and protein-protein interaction networks, besides providing the heat map diagram of the selected gene(s) in an organism across microarray expression experiments from either single or multiple studies. These features aid to the data interpretation in an integrative way. T2D-Db is to our knowledge the first publicly available resource that can cater to the needs of researchers working on different aspects of type 2 diabetes mellitus.

Indexed as

Databases, Nucleic AcidUser-Computer InterfaceAnimalsDiabetes Mellitus, Type 2Expressed Sequence TagsGene Expression ProfilingGenetic MarkersHumansMiceOligonucleotide Array Sequence AnalysisPolymorphism, Single NucleotideProtein Interaction MappingRatsRisk FactorsGenetic Markers

Identifiers

PMID18605991
PMCPMC2491641
OpenAlexW2148987786

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.