AI-Assisted Life Science

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Protein Imaging with Cryo-EM

Cryo-EM freezes, captures, and stacks thousands of images to visualize proteins and molecules. RELION's deep learning algorithm develops 3D structures by stacking cryo-EM datasets.

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Biomolecular Simulation

Molecular Dynamics applications simulate molecular tendencies helping scientists analyze atomic behavior. Deep learning and AI accelerate large simulations in granular detail.

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Future Protein Prediction

Some proteins are difficult to image with cryo-EM. Recently developed AlphaFold2 and RoseTTAFold use AI neural networks to accurately model protein from their amino acid sequence.

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AMD Ryzen 7000 Series Dual GPUWorkstation


Starting at


CPU1x AMD Ryzen 7000 Series Processor
GPUUp to 2x NVIDIA RTX 6000/5000/4500 Ada, 1x RTX 4090/4080, and more
MEM32GB DDR4 Memory [Up to 128GB]
STO3x M.2 + 6x 3.5" + 2x2.5" Internal Drives
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AMD Threadripper PRO Quad GPUWorkstation


Starting at


CPU1x AMD Ryzen Threadripper PRO 5000WX
GPUUp to 4x NVIDIA RTX 6000/5000/4500 Ada, 2x RTX 4090/4080, and more
MEM128GB DDR4 ECC (Up to 1TB)
STO2x M.2 + 6x 3.5" + 2x 2.5" Internal Drives
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Dual Xeon Scalable Multi-GPUWorkstation


Starting at


CPU2x 3rd Gen Intel Xeon Scalable Series
GPUUp to 4x NVIDIA RTX 6000, 5000, 4500 Ada, and more
MEM256GB DDR4 ECC (Up to 2TB)
STO8x 3.5" Hot-swap + 2x M.2 Slots

Recently Discovered and Recognized

Protein Folding and AI Assisted Prediction

What is Protein Folding?

Proteins are the working molecules that perform vast functions in every living cell and are made up of long chains of amino acids that have a 1-to-1 correlation to how proteins fold. Its 3D shape dictates the properties of a protein and being able to predict how new proteins fold helps scientists determine its functions.

Protein Folding with AI

AI-powered algorithms RoseTTAFold and AlphaFold 2 enable the prediction of protein 3D structures with high confidence. By revealing a protein structure and how it folds, scientists can understand how proteins function and interact. The breakthrough could see significant advancements in drug discovery and material science.

Parsing through Millions of Data Points

Genomics Diagnostics

Genomics Sequencing and Modification?

Genomics is the study of molecular biology that specifically targets the structure, order, function, and mapping of genome and DNA. Whole-genome sequencing can help identify the genetic cause of a disease, which help scientists potentially modify and correct genomes for the best treatments.

AI in Genomics

AI applications in the genomics space vary from variant analysis of diseased cells, genetic editing of faulty DNA, or even universal and personal drug discovery. With modern, advanced ML/DL, multiple layers of information can help sort the human genome much finer and more in-depth, in as little as 7 hours versus weeks.

Applications for AI Accelerated Genomics

Solutions with NVIDIA RAPIDS and NVIDIA CLARA; with applications for medical devices (Clara Holoscan), genomics (Clara Parabricks), drug discovery (Clara Discovery), and more; give way for AI accelerated genomics to potentially and fundamentally change critical care and patient diagnosis.

Molecular Dynamics and HPC

What is Molecular Dynamics?
Molecular Dynamics is the study of atoms and molecules using computers to simulate atomic interactions between molecules. By helping scientists assist in protein folding and identify structural molecular changes, MD simulations are essential to running molecular experiments that are expensive, difficult, or even impossible in the real world.
AI Deep Learning and HPC Application
Molecular Dynamics simulations have been around since the 1970s but were only performed on a small scale. Today, molecular simulations can include over 20 million atoms and exceed 20 million calculations. Applications like AMBER, GROMACS, NAMD, and RELION are constantly being updated to include new ways to experiment with different molecules in different mediums.
Future of Molecular Dynamics
By incorporating AI and Deep Learning, molecular simulations can continue to be executed faster and faster. As computers begin to simulate molecular tendencies with extreme accuracy, scientists can gain valuable insight into granular atomic properties to test and advance synthetic proteins and molecules.