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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
Combinatorial barcoding technology revolutionizes the outdated limitations of traditional single-cell methodologies. By eliminating the need for specialized instruments, it empowers researchers to make groundbreaking discoveries with ease. This innovation allows for the profiling of anywhere from 1,000 to 1 million cells or nuclei in a single experiment, driving forward unparalleled advancements in science. Evercode combinatorial barcoding technology significantly outperforms droplet-based methods, enabling researchers to increase the scale of their experiments without the constraints of previous technologies. Enjoy enhanced data quality while avoiding the complexities and requirements of outdated hardware. Conduct single-cell experiments using only a pipette and standard laboratory tools, simplifying the process and making it more accessible. The split-pool combinatorial barcoding technique facilitates scalable single-cell analysis without relying on any specialized instruments, making it easier than ever to achieve scalable sequencing. Each kit includes a comprehensive set of reagents and user-friendly analysis software, streamlining the entire workflow from start to finish for optimal efficiency. This technology not only enhances research capabilities but also fosters a new era of accessibility in scientific exploration.
API Access
Has API
API Access
Has API
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
Parse Biosciences
Founded
2018
Country
United States
Website
www.parsebiosciences.com