COMBAT-TB-NeoDB: fostering tuberculosis research through integrative analysis using graph database technologies.

Thoba Lose, Peter van Heusden, Alan Christoffels

Abstract read

In one paragraph

Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it

0cells of the map it votes in

3citing 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

3 citing papers in PubMed.

MTB-ImmunogenKG: An LLM-assisted knowledge graph for antigen selection in tuberculosis vaccine research.Biosafety and health · 2026
Article
The COMBAT-TB Workbench: Making Powerful Mycobacterium tuberculosis Bioinformatics Accessible.mSphere · 2022
Article
Applied Bioinformatics and Public Health Microbiology: challenges, discoveries and innovations during a pandemic.Microbial genomics · 2022
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

3 authors.

Thoba LoseSouth African National Bioinformatics Institute, South African MRC Bioinformatics Unit, University of the Western Cape, Bellville, 7535, South Africa.

Peter van HeusdenSouth African National Bioinformatics Institute, South African MRC Bioinformatics Unit, University of the Western Cape, Bellville, 7535, South Africa.

Alan ChristoffelsSouth African National Bioinformatics Institute, South African MRC Bioinformatics Unit, University of the Western Cape, Bellville, 7535, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationRecent advancements in genomic technologies have enabled high throughput cost-effective generation of 'omics' data from M.tuberculosis (M.tb) isolates, which then gets shared via a number of heterogeneous publicly available biological databases. Albeit useful, fragmented curation negatively impacts the researcher's ability to leverage the data via federated queries.

resultsWe present Combat-TB-NeoDB, an integrated M.tb 'omics' knowledge-base. Combat-TB-NeoDB is based on Neo4j and was created by binding the labeled property graph model to a suitable ontology namely Chado. Combat-TB-NeoDB enables researchers to execute complex federated queries by linking prominent biological databases, and supplementary M.tb variants data from published literature. AVAILABILITY AND IMPLEMENTATION: The Combat-TB-NeoDB (https://neodb.sanbi.ac.za) repository and all tools mentioned in this manuscript are freely available at https://github.com/COMBAT-TB. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Mycobacterium tuberculosisTuberculosisDatabases, FactualGenomeGenomicsHumansSoftware

Identifiers

PMID31504165

DOI10.1093/bioinformatics/btz658

PMCPMC9883708

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

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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.