Fatty Acid Degradation Gene Expression Data for Osteoarthritis Biomarker Discovery

Six hub genes (APOD, COL1A1, SULF1, CHI3L1, PENK, ADM) were identified as potential diagnostic biomarkers for osteoarthritis using machine learning and bioinformatics. The 29.4 MB dataset, authored by Jian Li and last updated in April 2026, contains results from analyses of publicly accessible OA-related datasets and fatty acid degradation-associated genes. It includes findings on immune cell infiltration correlations and 28 potential therapeutic drugs targeting the identified hub genes.

Use Cases

• Validate diagnostic biomarkers for osteoarthritis based on the six identified hub OA-FADEGs.
• Analyze correlations between fatty acid degradation genes and immune cell infiltration in OA samples.
• Screen for potential therapeutic drugs targeting specific gene signatures using the DSigDB database.
• Replicate machine learning workflows for identifying disease-associated differentially expressed genes.

Strengths

• Identifies six specific hub genes (APOD, COL1A1, SULF1, CHI3L1, PENK, ADM) with strong diagnostic efficacy for OA.
• Results were verified by qRT-PCR, suggesting experimental validation.
• Analysis includes 28 potential therapeutic drugs identified via the Drug Signatures Database (DSigDB).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale modeling.
• Data may reflect bias inherent to the specific publicly accessible databases used in the study.

Provenance

Source

figshare, author Jian Li.

Collection Method

OA-related datasets and FAD-associated genes were retrieved from publicly accessible databases, analyzed with multiple bioinformatics and machine learning methods.

Time Range

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Freshness

Last updated 2026-04-16 05:24:43; freshness should be verified.

Geography

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