Results for “ipynb”

Guides creating clean, reproducible Jupyter notebooks with structured workflows, best practices, and IPython magic for analysis and presentation.

Create, review, debug, test, or reproduce Python Jupyter notebooks by inspecting format, executing cells top-to-bottom in a clean kernel, and verifying outputs.

Apply medicinal chemistry filters for compound triage: drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and a custom query language for library filtering.

Filters and prioritizes compound libraries in drug discovery using drug-likeness rules, structural alerts, complexity metrics, and a query language.