Electrochemical Aptamer Sensor Data for Progesterone and 40 Interferents

20,000 voltammograms from automated electrochemical experiments screening a steroid-binding aptamer against progesterone and 40 diverse interferent molecules. The dataset was generated by Emily Carroll and published on figshare in May 2026. It was used to investigate how molecular hydrophobicity influences aptamer cross-reactivity.

Use Cases

• Training machine learning models to predict sensor cross-reactivity based on molecular descriptors like hydrophobicity.
• Benchmarking automated electrochemical platforms for high-throughput sensor characterization.
• Informing aptamer counterselection and design processes to improve sensor specificity.
• Analyzing the relationship between electrochemical signal frequency and optimal sensor interrogation parameters.

Strengths

• Contains 20,000 voltammograms, demonstrating high experimental throughput.
• Screens a scope of 40 structurally and functionally diverse interferent molecules.
• Experimental throughput was improved 3-fold over manual methods, enhancing reproducibility.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data is specific to a single aptamer and progesterone as a test case; generalizability to other targets is untested.

Provenance

Source

Emily Carroll via figshare.

Collection Method

Data collected using an automated electrochemistry platform for titration and frequency mapping experiments.

Freshness

Last updated 2026-05-21 09:32:51; freshness should be verified.