Generate protein sequences and predict structures with ESM3 and ESM C models.
npx skills add https://github.com/JosephWoodall/noosphere --skill esm-josephwoodall
Please help me install this Agent Skill. Skill: esm Source: https://github.com/JosephWoodall/noosphere/tree/main/.agent/skills/esm Command: npx skills add https://github.com/JosephWoodall/noosphere --skill esm-josephwoodall
ESM provides accessible, state-of-the-art protein language models for generating sequences, predicting structures, and extracting embeddings, enabling researchers to design proteins and analyze their functions without building models from scratch.
Generate a complete protein sequence and predicted structure for a target design using ESM3.
High-intent search queries and answers about installing and using this skill.
Protein inverse folding and structure prediction use ESM3 to design sequences folding into target structures. Researchers leverage multimodal capabilities covering sequence, structure, and function tracks to generate and evaluate novel protein designs.
Protein embeddings for classification and clustering are extracted using ESM C models. These representations enable downstream similarity search and functional analysis without requiring researchers to build models from scratch.
ESM3 protein design workflows support Forge API integration for cloud-scale inference. This enables production-grade throughput and collaboration, allowing researchers to execute sequence generation and function conditioning remotely.
Setting up ESM for protein design requires the esm family models alongside Python tooling like torch, numpy, and requests. These dependencies enable local inference and Forge API integration for multimodal sequence generation.
Function-conditioned generation in ESM3 uses multi-track workflows to design proteins across sequence, structure, and function. This chain-of-thought design pattern allows researchers to specify functional constraints when generating novel proteins.
ESM3 handles multimodal protein generation and inverse folding across sequence and structure tracks, while ESM C focuses on extracting embeddings for classification and similarity search. Both provide state-of-the-art representations without building models from scratch.
SologaGenerate protein sequences and embeddings with ESM3 and ESM C.
shushuznGenerate and analyze protein sequences, structures, and annotations with ESM3.
qinyan-aiDesign, analyze, and embed proteins with ESM3 and ESM C models.
jimmc414Generate protein sequences and extract embeddings using ESM3 and ESM C.
