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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Evo 2 represents a cutting-edge genomic foundation model that excels in making predictions and designing tasks related to DNA, RNA, and proteins. It employs an advanced deep learning architecture that allows for the modeling of biological sequences with single-nucleotide accuracy, achieving impressive scaling of both compute and memory resources as the context length increases. With a robust training of 40 billion parameters and a context length of 1 megabase, Evo 2 has analyzed over 9 trillion nucleotides sourced from a variety of eukaryotic and prokaryotic genomes. This extensive dataset facilitates Evo 2's ability to conduct zero-shot function predictions across various biological types, including DNA, RNA, and proteins, while also being capable of generating innovative sequences that maintain a plausible genomic structure. The model's versatility has been showcased through its effectiveness in designing operational CRISPR systems and in the identification of mutations that could lead to diseases in human genes. Furthermore, Evo 2 is available to the public on Arc's GitHub repository, and it is also incorporated into the NVIDIA BioNeMo framework, enhancing its accessibility for researchers and developers alike. Its integration into existing platforms signifies a major step forward for genomic modeling and analysis.

Description

Profluent's innovative platform transforms the field of protein design by seamlessly combining cutting-edge AI technology with its own experimental capabilities, allowing for the development of proteins that are either inspired by nature or entirely newly conceived. This comprehensive methodology provides precise, flexible, and scalable solutions to intricate biological problems, resulting in advancements that push the boundaries of protein functionality. Profluent's foundational models extend protein design beyond the constraints of traditional random approaches, enabling the simultaneous optimization of various characteristics, enhancing sequence diversity, and unlocking new functionalities. By venturing into unexplored protein territories, Profluent presents distinctive opportunities that surpass the limitations of natural or patented proteins, streamlining the process for partners to achieve commercial viability in a more cost-effective and accessible manner. Underpinning Profluent's capabilities is a strong dedication to scientific excellence, utilizing a wide range of datasets and advanced AI techniques to address complex challenges effectively. As a result, Profluent not only advances protein engineering but also sets a new standard in the industry, fostering innovative collaborations and breakthroughs.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

BioNeMo
Evo Designer
GitHub
Hugging Face

Integrations

BioNeMo
Evo Designer
GitHub
Hugging Face

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Arc Institute

Country

United States

Website

arcinstitute.org/tools/evo

Vendor Details

Company Name

Profluent

Founded

2022

Country

United States

Website

www.profluent.bio/platform

Product Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Alternatives

Alternatives

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