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What is Galaxy?

Galaxy is an open-source, web-oriented platform tailored for managing data-rich research within the biomedical sector. New users are encouraged to start with the basic introductory resources or seek out the extensive help options available to them. Additionally, it is possible to establish a personal instance of Galaxy by following a comprehensive tutorial while choosing from a broad selection of tools provided in the tool shed. The current operational Galaxy instance benefits from the infrastructure offered by the Texas Advanced Computing Center. Moreover, further resources can be accessed through the Jetstream2 cloud, which is enabled by ACCESS and backed by the National Science Foundation. Researchers have the ability to quantify, visualize, and summarize discrepancies found in deep sequencing datasets while also constructing maximum-likelihood phylogenetic trees. The platform also facilitates phylogenomic and evolutionary tree construction with multiple sequences, enables the clustering of matching reads using the TN-93 method, and allows for the exclusion of sequences from a reference within a designated distance of a cluster. Additionally, researchers can perform maximum-likelihood estimations to determine gene essentiality scores, reinforcing Galaxy's status as an invaluable instrument for diverse genomic research applications. With its robust capabilities and user-friendly design, Galaxy continues to advance the frontiers of biomedical research.

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

Arch
CoinRoutes
Evo Designer
GitHub
Hugging Face
Inn-Flow
Lybra Assistant
NVIDIA BioNeMo

Integrations Supported

Arch
CoinRoutes
Evo Designer
GitHub
Hugging Face
Inn-Flow
Lybra Assistant
NVIDIA BioNeMo

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Galaxy

Company Location

United States

Company Website

usegalaxy.org

Company Facts

Organization Name

Arc Institute

Company Location

United States

Company Website

arcinstitute.org/tools/evo

Categories and Features

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