HAL (France)
open access
CRISPRidentify: identification of CRISPR arrays using machine learning approach
Abstract CRISPR–Cas are adaptive immune systems that degrade foreign genetic elements in archaea and bacteria. In carrying out their immune functions, CRISPR–Cas systems heavily rely on RNA components. These CRISPR (cr) RNAs are repeat-spacer units that are produced by processing of pre-crRNA, the t
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
- Screening disease feature genes and analyzing correlations with immune cell infiltration in knee osteoarthritis chondrocytes based on multiple machine learning algorithms#285417
- Multiple approaches for CRISPR-based targeting of DNA methylation to promoters of bacterial and viral susceptibility genes in cassava#341937
- Identification of Key Biological Pathways and Genes in Multiple Sclerosis Via Integrating Domain Knowledge Into the Machine Learning Model#336789
- Generation of Leucine-rich repeat kinase 2 (LRRK2) knockout neuroblastoma cells SH-SY5Y by CRISPR/Cas9-mediated genome editing#413456
- Inhibitors of crispr-cas9 — The Regents Of The University Of California (US20230287058A1)#607478
Record · ID 1219264
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