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Healthcare and Life Sciences

This page describes the collection of Healthcare and Life Sciences software on HiperGator. Artificial intelligence (AI), including machine learning (ML), has the potential to revolutionize human health and medical research by enabling software to learn from past examples and make informed decisions in life sciences. The Research Computing AI Support team will assist in developing and refining advanced models for various tasks in healthcare and life science, including medical image analysis, disease detection, and genomic data interpretation. For assistance, reach out via support requests or consulting.

Deep Learning Frameworks

There are preinstalled and configured environments on HiPerGator for the most frequently used deep learning frameworks, including TensorFlow, Pytorch, and MXNet.

Customizing Conda Environments

Users can create custom conda environments on HiPerGator.

Domain-Specific Frameworks and Tools for Healthcare and Life Sciences

Below are several frameworks and tools configured for training deep learning models on HiPerGator-AI.

  • AlphaFold: AlphaFold is an AI software developed by DeepMind that predicts protein structures. Using deep learning algorithms, it predicts protein structures with remarkable accuracy, down to atomic levels. The software constructs an initial model, iteratively refines it, and produces a 3D model of the protein. The final output includes 3D coordinates for every non-hydrogen atom in the protein, along with confidence levels for each amino acid residue.

  • BioNeMo: NVIDIA BioNeMo is a generative AI platform for drug discovery that simplifies and accelerates the training of models using your own data and scales the deployment of models for drug discovery applications.

  • Clara Parabricks: NVIDIA Parabricks is a scalable genomics analysis software suite that leverages full-stack accelerated computing to process data in minutes. Compatible with all leading sequencing instruments, it supports diverse bioinformatics workflows and integrates AI for accuracy and customization.

  • MONAI core: MONAI Core is a PyTorch-based, open-source framework for deep learning in healthcare imaging, part of the PyTorch Ecosystem. See MONAI Core tutorials for more information.

  • MONAI label: MONAI Label is an intelligent open-source image labeling and learning tool that enables users to create annotated datasets and build AI annotation models. It reduces the time and effort of annotating new datasets and enables the adaptation of AI to the task at hand by continuously learning from user interactions and data.

    • Use the command below to list the available versions on HiPerGator-AI. Refer to recorded MONAI Label tutorials for details: 
      module spider ngc-monailabel