Orchestrate cloud-native molecular modeling workflows via the Rowan Python API.
npx skills add https://github.com/crazymsn/academic-skills --skill rowan-crazymsn
Please help me install this Agent Skill. Skill: rowan Source: https://github.com/crazymsn/academic-skills/tree/main/academic-skills/rowan Command: npx skills add https://github.com/crazymsn/academic-skills --skill rowan-crazymsn
Rowan enables researchers and teams to run cloud-native molecular modeling workflows without maintaining local HPC infrastructure or GPU provisioning. It provides a unified Python API to orchestrate complex tasks across compute resources.
Install the Rowan client, configure your API key, and run your first workflow with a single call such as submitting a descriptors workflow for a SMILES input.
High-intent search queries and answers about installing and using this skill.
Run cloud-based molecular modeling workflows without local HPC infrastructure by using a unified Python API to orchestrate pKa predictions, docking, and conformer searches across remote compute resources.
Yes, you can batch screen pKa and macropKa predictions programmatically by submitting SMILES inputs through the Python API to generate scalable prediction campaigns on cloud resources.
Yes, Python 3.12 or higher is required to run conformer and tautomer ensemble generation, along with a valid API key to authenticate and access the cloud-native compute environment.
The best way to organize large-scale docking campaigns in the cloud is by utilizing project and folder organization features alongside webhook integrations to manage usage controls and scalable execution.
Protein-ligand cofolding works alongside MSA generation workflows, enabling researchers to submit integrated molecular modeling tasks through a single Python API for comprehensive structural analysis.
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