AI-Powered Biomedical Research Engine

Weeks of research,
done in minutes.

GLKB synthesizes biomedical literature into structured, evidence-
backed answers. Every claim links directly to its source paper.

GLKB API Docs
https://glkb.org/
A GLKB answer with its citations

Trusted by the biomedical researchers at:

From query to answer

How GLKB Works

  1. 1

    Ask

    Type any biomedical query: a gene, variant, drug target, or disease.

  2. 2

    Retrieve

    GLKB searches 263M terms and 14.6M relationships, surfacing the most relevant PubMed papers.

  3. 3

    Reason

    The AI synthesizes retrieved evidence into a structured, concise, cited answer.

  4. 4

    Verify

    Every claim links to a PubMed ID. Gaps are labeled "none found" and never fabricated.

By researcher, for researcher

What Makes GLKB Different

Evidence, not estimates

General LLMs can't tell you when they're guessing. GLKB grounds every answer in retrieved literature: your synthesis only reflects what the evidence actually says. Where support is missing, GLKB labels it "none found" rather than filling it in with plausible-sounding fabrications. That transparency is the feature.

A citation list with its source sentences

Biomedical-native

Built on the full PubMed corpus: 263M biomedical terms and 14.6M relationships across gene-disease associations, pathways, and ontology hierarchies.

Reproducible by design

Same query, same results. Outputs are structured, machine-readable, and consistent across, making them suitable for publication-grade workflows.

Built for scale

Analyze hundreds of targets, variants, or genes in parallel. Structured, cited outputs feed directly into your downstream pipeline.

The Knowledge Graph

Visualize what
the literature knows and
where the gaps are.

Explore connections between genes, diseases, drugs, and pathways, then jump directly to the supporting papers. Not just what science has established, but where the evidence runs thin.

A knowledge graph linking genes, diseases, drugs and variants

Use cases

Built for Your Research

Connect mechanistic studies, human genetic evidence, pharmacological findings, and clinical development to understand the biological rationale for a candidate target.

Q: What is known about DYRK1A as a therapeutic target in type 2 diabetes?

DYRK1A in type 2 diabetes (T2D): what’s known

1) Rationale: β-cell failure in T2D makes β-cell regeneration attractive

A major therapeutic idea in T2D is to increase functional pancreatic β-cell mass. Multiple groups have identified DYRK1A inhibition as a way to unlock adult human β-cell cell-cycle entry, a process that is normally very limited.

2) Key experimental evidence supporting DYRK1A as a target

  • Harmine and DYRK1A/NFAT axis (foundational evidence) A high-throughput screen identified harmine analogs as human β-cell mitogens, and the study proposes DYRK1A as the likely target with NFAT transcription factors as mediators, with in vivo models showing increased β-cell proliferation, increased islet mass, and improved glycemic control 1.
  • More robust proliferation via combination strategies (DYRK1A + TGFβ/SMAD pathway inhibition) DYRK1A inhibitors alone drive modest proliferation; combining DYRK1A inhibition with TGFβ superfamily/SMAD pathway inhibition yielded substantially higher adult human β-cell proliferation and increased β-cell numbers, while noting preservation of differentiated function, and including β cells from people with T2D 3.
  • Synergy with existing T2D drug class (GLP-1 receptor agonists + DYRK1A inhibitors) GLP-1R agonists don’t typically increase human β-cell proliferation, while DYRK1A inhibitors do but modestly and with limited β-cell specificity. Combining the two classes synergistically increased human β-cell replication, increased β-cell numbers, and extended to improved insulin secretion and glycemic control in mouse transplantation models; effects were also seen in β cells from individuals with T2D 4.
  • Small-molecule series consistent with DYRK1A being a key driver Aminopyrazine compounds (described as acting via combined DYRK1A and GSK3B inhibition) stimulated robust proliferation in adult human islets and improved glycemic control in diabetic mice, with multiple lines of evidence pointing to Dyrk1a as the key target 2.

3) What the GLKB knowledge graph shows (structured vs. literature co-mention)

In GLKB, there is no curated GeneToDiseaseAssociation edge recorded between DYRK1A and T2D (i.e., not a genetics/causal association entry in the KG for this pair).

But DYRK1A and “Diabetes Mellitus, Type 2” co-occur in the literature with 14 articles captured as co-mentions (GLKB Cooccur edge; source PubMed).

4) Therapeutic implications and main open challenges

Most mature concept: DYRK1A inhibition as a β-cell regenerative strategy (alone or in combinations).

Key translational challenges repeatedly implied by the experimental literature:

Achieving β-cell specificity (DYRK1A is broadly expressed; systemic inhibition raises off-target risk).

Ensuring durable function and avoiding unwanted proliferation/dedifferentiation (some studies explicitly test for preserved β-cell differentiated function in combinations).

Moving from short-term in vivo models (often islet transplant systems) to longer-term safety/efficacy studies.ng additional inhibitor series and any emerging early clinical programs, if present).

+24.8%
Accuracy improvement on PubMedQA-HC
263M
Biomedical terms in the knowledge graph
14.6M
Relationships encoded
~30 min
To process 1,500 candidate genes with full citations

Behind GLKB

The Team

GLKB is built by a multidisciplinary team at the intersection of AI, biomedical research, and knowledge systems at the University of Michigan, Ann Arbor.

Frequently Asked Questions

What is GLKB?

GLKB is an AI-powered research platform that helps you search, analyze, and synthesize scientific literature faster. Instead of manually reading multiple papers, GLKB surfaces key insights, summarizes findings, and helps you connect ideas across studies.

GLKB is built on publicly available scientific literature, with a primary focus on PubMed-indexed research. We process and structure this content to make it easier to search, analyze, and synthesize key insights across studies.

GLKB performs deep analysis across multiple research papers, which can take longer than a typical search. Response times may vary depending on query complexity and system load. Occasionally, errors can occur due to limitations in data availability or processing. If that happens, we recommend refining your query or trying again. Our system is continuously improving to deliver faster and more reliable results.

GLKB primarily works with abstracts and available structured data from scientific publications. When full-text content is accessible, it may also be incorporated to enhance analysis and provide more detailed insights.

GLKB uses advanced AI models to analyze scientific content and generate structured insights. This includes summarizing papers, identifying key findings, and answering follow-up questions based on the literature.

GLKB is designed to provide transparent and research-grounded outputs. Wherever possible, responses are tied back to source literature. However, like any AI tool, results should be reviewed and validated, especially for critical academic or professional use.

GLKB reduces the time spent searching and reading by surfacing key insights instantly. It helps you understand complex topics faster, identify patterns across studies, and focus more on thinking, not just gathering information.

You can explore summaries, ask follow-up questions, compare findings across papers, and export results for your own research workflow. GLKB is built to support the full research process, from discovery to insight.

Yes. The expiration of your queries depends on your current plan. Free and purchased queries follow the same expiration policy as your subscription to ensure consistent usage and system performance.

Yes. GLKB offers a free plan that allows you to explore the platform with limited queries and features. You can upgrade at any time for more access and advanced capabilities.

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