Protein Genesis AI v2

Unlock the potential of protein design with AI-driven sequence generation.

Automated product research from public website content. No hands-on app test is recorded for this profile. Pricing source and check date are shown below where available.

Research fitSource-based assessment: ProteinGenesis offers an accessible, AI-driven platform on Hugging Face for generating novel protein sequences, ideal for early-stage research and design.

ProteinGenesis is a Hugging Face Space that leverages AI to generate novel protein sequences. It provides a user-friendly interface for researchers and scientists to explore and design new proteins, potentially accelerating drug discovery and biotechnology innovations.

Visit Protein Genesis AI v2

Key Features:

AI-powered protein sequence generation
Hosted on Hugging Face Spaces for easy access
Interactive interface for input and output
Leverages underlying ML models for biological design
Community-driven development and sharing

Pros

Biotechnology researchers needing to design new proteins
Drug discovery scientists exploring novel therapeutic targets
Academics studying protein evolution and function

Cons

Performance depends on Hugging Face Space's allocated hardware
Requires an understanding of protein biology to interpret results
May incur costs for advanced hardware usage on Hugging Face

Pricing

freemiumFree tier

Starting at:$0.03/hour

Free tier:Basic CPU hardware for Spaces, limited ZeroGPU quota, $0.10 monthly credits for Inference Providers

Plans

Free: Basic CPU, limited ZeroGPU, $0.10 monthly credits
PRO $9/month: 10x private storage, 2x public storage, 20x inference credits, 8x ZeroGPU quota, host Spaces
Team $20/month per user: SSO, data location control, audit logs, granular access, analytics, advanced auth, centralized tokens, create Spaces with advanced compute
Enterprise $50/month per user: All Team benefits, highest limits, SCIM, advanced security, managed billing, dedicated support

Categories:

Research & Science AI Infrastructure

Tags:

protein design sequence generation biotechnology drug discovery hugging face spaces machine learning bioinformatics

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Quick Decision

Try if: You are a researcher or scientist in biotechnology or drug discovery looking for an accessible, AI-powered tool to generate novel protein sequences without managing complex infrastructure.

Skip if: You require protein structure prediction rather than sequence generation, or you need a tool with guaranteed high-performance compute without considering potential costs.

Not for: Users without a basic understanding of protein science; Individuals looking for protein structure prediction (rather than sequence generation)

Trust Signals

Team Size
large

Tech Details

Platforms

web

Open Source

Yes

Support

Channels

forumdiscordgithub

Company

Name
Hugging Face
Location
New York, NY

Hugging Face is an AI company that builds tools for machine learning, including a platform for sharing models, datasets, and applications.

FAQ

Is ProteinGenesis free to use?

ProteinGenesis is hosted on Hugging Face Spaces, which offers a free tier with basic CPU hardware and limited ZeroGPU quota. More powerful hardware and increased usage will incur costs based on Hugging Face's pricing model for Spaces and Inference Endpoints.

What kind of hardware does ProteinGenesis run on?

ProteinGenesis can run on various hardware configurations offered by Hugging Face Spaces, ranging from free CPU Basic instances to powerful Nvidia GPUs (T4, L4, L40S, A10G, A100, H200, RTX PRO 6000) and custom accelerators like AWS Inferentia2 and Google TPU v5e. The choice of hardware impacts performance and cost.

How does ProteinGenesis generate protein sequences?

While the specific AI model used by ProteinGenesis is not detailed in the provided content, it leverages underlying machine learning models hosted on Hugging Face to generate novel protein sequences. Users interact with the model through a web-based interface.

Use Cases

Biotechnology researchers needing to design new proteins
Drug discovery scientists exploring novel therapeutic targets
Academics studying protein evolution and function