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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

VSClinical facilitates the clinical analysis of genetic variants in accordance with ACMG and AMP guidelines. Its structured workflow supports adherence to the American College of Medical Genetics (ACMG) standards, which are essential for identifying and categorizing pathogenic variants related to inherited disease risk, cancer susceptibility, and rare disease diagnosis. The combined ACMG/AMP guidelines for variant interpretation establish a framework for scoring variants and categorizing them into one of five classification levels. Implementing these guidelines necessitates a thorough examination of annotations, genomic contexts, and pre-existing clinical insights for each variant. VSClinical streamlines this process by offering a customized workflow that evaluates each relevant criterion and supplies comprehensive bioinformatics, literature references, and clinical knowledgebase evidence to aid in the scoring and interpretation of variants. This innovative approach is designed to enhance the efficiency of variant scientists as they navigate the complexities of variant processing and analysis. Overall, VSClinical stands out as a vital tool for accelerating the understanding and classification of genetic variants in clinical settings.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Evo Designer Yes 
GenomeBrowse No 
GitHub Yes 
Hugging Face Yes 
NVIDIA BioNeMo Yes 
VarSeq No 

Integrations

Evo Designer No 
GenomeBrowse Yes 
GitHub No 
Hugging Face No 
NVIDIA BioNeMo No 
VarSeq Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
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) No 
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 Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Arc Institute

Country

United States

Website

arcinstitute.org/tools/evo

Vendor Details

Company Name

Golden Helix

Founded

1998

Country

United States

Website

www.goldenhelix.com/products/VarSeq/vsclinical.html

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