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What is YASARA?

YASARA is a comprehensive software solution for molecular graphics, modeling, and simulation that has been available since 1993 and operates seamlessly across various platforms, including Windows, Linux, MacOS, and Android, aimed at making scientific inquiries more accessible. With an intuitive interface and impressive photorealistic graphics, it supports cost-effective virtual reality headsets, shutter glasses, and autostereoscopic displays, creating an engaging environment that allows users to focus on their research without the software becoming a distraction. Central to YASARA’s functionality is its Portable Vector Language (PVL), a cutting-edge development framework that offers performance levels significantly higher than traditional programs. This powerful framework enables users to visualize intricate protein structures and conduct authentic interactive simulations with accurate force fields on standard computers, while also taking advantage of GPU resources when available. By allowing users to actively manipulate molecules and interact with dynamic models rather than merely observing static representations, YASARA marks a pivotal enhancement in the realm of molecular modeling technology. This interactive capability not only enriches the educational process but also inspires users to delve deeper into the complexities of molecular interactions, ultimately broadening their understanding of scientific phenomena. As a result, YASARA fosters a more engaging and productive research experience for professionals and students alike.

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

Evo Designer
GitHub
Hugging Face
NVIDIA BioNeMo
Python

Integrations Supported

Evo Designer
GitHub
Hugging Face
NVIDIA BioNeMo
Python

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

YASARA

Date Founded

1993

Company Location

Austria

Company Website

www.yasara.org

Company Facts

Organization Name

Arc Institute

Company Location

United States

Company Website

arcinstitute.org/tools/evo

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