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features
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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

Utilize GenomeStudio Software to visualize and analyze data produced on Illumina array platforms, which provides an advanced solution for genotyping microarray data. This robust toolset offers performance-enhanced capabilities and an intuitive graphical interface, allowing for swift and effortless transformation of data into insightful outcomes. You can examine SNP and CNV data through a comprehensive array of 5 million markers and probes, identify sample outliers, and investigate differentially expressed genes among various genomes. Additionally, it facilitates the profiling of miRNA expression and allows you to merge mRNA with microRNA data within a single project. The software also enables the detection of cytosine methylation at single-base resolution and helps in identifying methylation patterns throughout the genome. At Illumina, we are dedicated to leveraging groundbreaking technologies to advance the analysis of genetic variations and functions, paving the way for research that was once beyond reach. Our commitment is to provide innovative, adaptable, and scalable solutions that effectively address our customers' diverse needs. Ultimately, this focus on innovation ensures that we remain at the forefront of genetic research, facilitating discoveries that can transform our understanding of biology.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Evo Designer Yes 
GitHub Yes 
Hugging Face Yes 
NVIDIA BioNeMo Yes 

Integrations

Evo Designer No 
GitHub No 
Hugging Face No 
NVIDIA BioNeMo No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person Yes 

Vendor Details

Company Name

Arc Institute

Country

United States

Website

arcinstitute.org/tools/evo

Vendor Details

Company Name

Illumina

Founded

1998

Country

United States

Website

www.illumina.com/techniques/microarrays/array-data-analysis-experimental-design/genomestudio.html

Product Features

Data Analysis

Data Discovery No 
Data Visualization No 
High Volume Processing No 
Predictive Analytics No 
Regression Analysis No 
Sentiment Analysis No 
Statistical Modeling No 
Text Analytics No 

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