Europe PMC
open access
FLiP-Z by Zimeck: A Python-Based Machine-Learning Tool for Predicting Fungicide-Likeness of Organic Molecules
Development of new agricultural fungicides requires reliable computational tools to screen candidate molecules before investing time, money, and effort in experimental assays. In this study, curated datasets of fungicidal and non-fungicidal compounds were employed in the construction of possible pre
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
- FLiP-Z by Zimeck: A Python-Based Machine-Learning Tool for Predicting Fungicide-Likeness of Organic Molecules#784617
- Semantic knowledge improves molecular machine learning for chemical toxicity prediction.#422908
- Machine Learning and Artificial Intelligence in Toxicology and Environmental Health#164185
- Applications of machine learning and artificial intelligence in toxicology and environmental health#10794
- Statistical and machine learning approaches for understanding infectious disease dynamics in response to environmental change: applications to emerging fungal diseases#642205
Record · ID 970777
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