Deutsche Nationalbibliothek
metadata only
Synthetic bacterial consortium for degradation of plastic pyrolysis oil waste: experimental optimization and neural network modeling / Yunpu Jia, Jingxi Dou, Hendrik Ballerstedt, Jianmin Xing, Lars M. Blank
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Artificial Intelligence-Assisted Discovery and Engineering of PET-Degrading Enzymes: From Data-Driven Protein Design to Sustainable Plastic Recycling#332221
- Interpretable convolutional neural networks for sequence-based classification and discovery of plastic-degrading enzymes.#214019
- Deep Learning-driven synergistic engineering of PET hydrolase for post-consumer PET depolymerization.#362547
- Convergent GenX biodegradation by genomically designed and functionally screened synthetic bacterial consortia.#354581
- CascadeMAP: Autonomous Closed-loop Optimization of Enzyme Cascades via Microfluidics, Machine Learning and Agentic AI#343603
Record · ID 629073
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive