# molecular composites

- **Event:** [Built with Claude: Life Sciences](https://cerebralvalley.ai/e/built-with-claude-life-sciences)
- **When:** Jul 7 at 12:00 PM – Jul 14 at 12:00 AM (EDT)
- **Where:** Online
- **Team:** [Melik Demirel](https://cerebralvalley.ai/u/MelikDemirel)
- **GitHub:** https://github.com/melikcdemirel/claude
- **Demo video:** https://youtu.be/QCd-Tl8T0KI
- **Gallery:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/84

Cadence is an AI copilot for the Learn phase of the synthetic-biology Design–Build–Test–Learn (DBTL) cycle. Four Claude-powered agents run the loop end to end; the Learn agent ingests Test-stage datasets, flags undefined, duplicated, and anomalous data tokens, and scores each with a reproducible confidence index that feeds fixes back into the next Design.

We validated it against a real study — Singhal, Allen, Gaddes, Baer & Demirel, "Biomanufacturability of a Squid Ring Teeth Protein Library via Orthogonal High-Throughput Screening" — whose thesis is that predictable biomanufacturing "runs through models learned from library-scale data." Given the per-bin summary behind the paper's Figures 5–6, the Learn agent reproduced its headline conclusions from the summary alone: FACS brightness saturates as a yield predictor (Cliff's δ +0.46 Low→Medium, −0.03 Medium→High), growth is not the bottleneck, and codon-adaptation index carries the residual signal (bin-mean CAI vs mCherry R² = 0.91). On a schema-faithful stand-in it also caught three data-integrity defects unprompted — a malformed column, an exact duplicate (r = 1.000), and a zero-variance feature.

The entire system — orchestration, bug fixes, the live run, and this write-up — was built with Claude (Cowork) in one session.

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Markdown version of https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/84. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt