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What is Photo51?

Photo51 is an innovative online platform dedicated to molecular biology, focusing on the design and analysis of DNA and protein sequences. This all-encompassing toolkit enables users to perform a wide range of functions, including plasmid design, automated feature annotation, virtual cloning, the development of PCR primers, and simulations of agarose gel electrophoresis. Users can import sequence files and take advantage of an integrated genome browser to explore reference genomes, analyze gene views, and export sequences for their specific projects. Additional functionalities include the design of guide RNA with PAM visualization, both pairwise and multiple sequence alignment, Sanger chromatogram viewing, protein alignment, and reverse translation capabilities. Furthermore, Photo51 encourages collaboration by providing shared team workspaces and maintaining a version history for ongoing projects, enhancing teamwork efficiency. The open-access genome browser allows for deeper exploration of genomic data, while subscription options offer advanced editing and analytical features. Tailored specifically for researchers, educators, and biotechnology teams involved in molecular biology, this platform streamlines workflows for a variety of scientific inquiries. With its diverse capabilities, Photo51 is not just a tool but a comprehensive resource that meets the evolving demands of the molecular biology community. This versatility makes it an indispensable asset for anyone engaged in molecular research or education.

What is Evo 2?

Evo 2 is an advanced genomic foundation model that excels in predicting and creating tasks associated with DNA, RNA, and proteins. Utilizing a sophisticated deep learning architecture, it models biological sequences with precision down to single-nucleotide accuracy, demonstrating remarkable scalability in both computational and memory resources as context length expands. The model has been trained on an impressive 40 billion parameters and can handle a context length of 1 megabase, analyzing an immense dataset of over 9 trillion nucleotides derived from diverse eukaryotic and prokaryotic genomes. This extensive training enables Evo 2 to perform zero-shot function predictions across a range of biological types, including DNA, RNA, and proteins, while also generating novel sequences that adhere to plausible genomic frameworks. Its robust capabilities have been highlighted in applications such as the design of efficient CRISPR systems and the identification of potentially disease-causing mutations in human genes. Additionally, Evo 2 is accessible to the public via Arc's GitHub repository and is integrated into the NVIDIA BioNeMo framework, which significantly enhances its availability to researchers and developers. This integration not only broadens the model's reach but also represents a pivotal advancement in the fields of genomic modeling and analysis, paving the way for future innovations in biotechnology.

Media

Media

Integrations Supported

Integrations Supported

Evo Designer
GitHub
Hugging Face
NVIDIA BioNeMo

API Availability

API Availability

Pricing Information

€5/month
Academic access is €5/month; commercial use is €50/month.
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

Fearless League

Date Founded

2023

Company Location

Netherlands

Company Website

fearlessleague.com

Company Facts

Organization Name

Arc Institute

Company Location

United States

Company Website

arcinstitute.org/tools/evo

Categories and Features

Bioinformatics

Not specified

Categories and Features

AI Models

Not specified

AI Science

Not specified

Bioinformatics

Not specified

Foundation Models

Not specified

Molecular Modeling

Not specified

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